FINE TUNING ULANG AI

Doc.md

@@ -6,6 +6,12 @@
 
 ---
 
+> [!IMPORTANT]
+> **📖 FRONT-END INTEGRATION GUIDE**:  
+> Untuk panduan teknis khusus tim Front-End (termasuk tipe TypeScript, Axios snippets, pemetaan Peta & progress bar), silakan merujuk langsung ke dokumen [FRONTEND_API_DOC.md](file:///c:/khusus%20project%20IT/Fine%20tuning%20ulang%20AI%20jakarta/waste-prediction-api/FRONTEND_API_DOC.md).
+
+---
+
 ## 📑 Table of Contents
 1. [Project Overview](#1-project-overview)
 2. [System Architecture](#2-system-architecture)
@@ -154,71 +160,85 @@ Rasio dekomposisi dihitung dinamis dari dataset historis, fallback ke standar re
 
 ## 4. API Reference
 
-###  `POST /api/v1/predict`
-**Deskripsi**: Generate prediksi volume sampah 1–30 hari ke depan untuk lokasi tertentu.
+### 1. `POST /api/v1/predict`
+**Deskripsi**: Menghasilkan prediksi volume timbulan sampah harian/jam-an untuk lokasi tertentu beserta analisis risiko logistik menggunakan model Amazon Chronos atau Gradient Boosting.
 
 #### Request Body
 ```json
 {
-  "hari_ke_depan": 7,
-  "prediksi_hujan_bmkg": 25.5,
-  "skala_keramaian": 0,
-  "nama_lokasi": "JIS",
-  "dari_tanggal": "06-01"
+  "forecast_days": 7,
+  "rainfall_mm": 25.5,
+  "event_scale": 0,
+  "location": "JIS",
+  "start_date": "2026-07-03",
+  "granularity": "daily",
+  "model_type": "gradient_boosting"
 }
 ```
 | Field | Type | Required | Description |
 |-------|------|----------|-------------|
-| `hari_ke_depan` | `int` | ✅ | Durasi prediksi (1–30 hari) |
-| `prediksi_hujan_bmkg` | `float` | ✅ | Estimasi curah hujan (mm). `0` = kering |
-| `skala_keramaian` | `int` | ✅ | Skala event manual (0–5). `0` = normal |
-| `nama_lokasi` | `string` | ✅ | Target lokasi: `JIS`, `GBK`, `Pasar Senen`, `Gang Sempit Tambora` |
-| `dari_tanggal` | `string` | ❌ | Tanggal mulai. Format: `YYYY-MM-DD`, `MM-DD`, atau `"1 Juni 2026"` |
+| `forecast_days` | `int` | ✅ | Durasi prediksi (1–30 hari) |
+| `rainfall_mm` | `float` | ✅ | Curah hujan (mm). `0` = Auto (mengambil ramalan cuaca dari Open-Meteo) |
+| `event_scale` | `int` | ✅ | Skala keramaian event buatan (0-5) |
+| `location` | `string` | ✅ | Target lokasi: `JIS`, `GBK`, `Pasar Senen`, `Gang Sempit Tambora` |
+| `start_date` | `string` | ❌ | Tanggal awal prediksi. Contoh: `2026-07-03` |
+| `granularity` | `string` | ❌ | Tingkat rincian: `daily` atau `hourly` (default: `daily`) |
+| `model_type` | `string` | ❌ | Algoritma: `gradient_boosting` atau `chronos` (default: `gradient_boosting`) |
 
 #### Response Success (200)
 ```json
 {
   "status": "success",
-  "message": "🟡 WARNING di JIS: Volume di atas rata-rata.",
-  "confidence_score": 0.94,
+  "message": "Normal conditions.",
+  "confidence_score": 0.9325,
   "data": {
     "prediction_results": [
       {
-        "tanggal": "2026-06-02",
-        "lokasi": "JIS",
-        "total_volume_ton": 1245.50,
-        "sisa_makanan_ton": 621.15,
-        "plastik_ton": 285.84,
-        "rekomendasi_truk": 125,
-        "status_risiko": "WARNING 🟡",
-        "info_event": "PRJ Opening @ JIExpo"
+        "date": "2026-07-03",
+        "location": "JIS",
+        "total_volume_ton": 140.70,
+        "organic_waste_ton": 70.17,
+        "plastic_waste_ton": 32.29,
+        "recommended_trucks": 29,
+        "risk_status": "SAFE",
+        "event_info": null,
+        "hourly_breakdown": null
       }
     ],
     "logistics_plan": {
-      "trucks_needed": 872,
-      "manpower": 2616,
-      "estimated_duration_hours": 1743.2,
+      "trucks_needed": 29,
+      "manpower": 87,
+      "estimated_duration_hours": 28.1,
       "efficiency_rate": "85% (Optimal)"
     }
   }
 }
 ```
 
-#### Error Responses
-| Status Code | Response | Cause |
-|-------------|----------|-------|
-| `400` | `{"detail": "Format tanggal tidak valid..."}` | Input tanggal tidak dikenali parser |
-| `500` | `{"detail": "Gagal memproses prediksi: ..."}` | Internal error / model crash |
-| `503` | `{"detail": "Model/Dataset belum siap."}` | Service masih startup / model loading |
+---
+
+### 2. `POST /api/v1/predict/csv`
+**Deskripsi**: Mengirimkan parameter yang sama seperti endpoint prediksi standar, tetapi menghasilkan output berkas CSV secara langsung untuk diunduh.
+
+#### Request Body
+Sama seperti `POST /api/v1/predict`.
+
+#### Response Success (200)
+Mengembalikan berkas file download (`text/csv`) dengan nama file dinamis: `waste_forecast_[Location]_[Days]d.csv`.
+**Header Respon**:
+`Content-Disposition: attachment; filename="waste_forecast_JIS_7d.csv"`
 
-###  `GET /`
-**Deskripsi**: Health check & metadata sistem.
+---
+
+### 3. `GET /status`
+**Deskripsi**: Health check status server dan ketersediaan model ML.
+#### Response Success (200)
 ```json
 {
   "status": "Online",
-  "model": "Chronos-T5 Tiny",
-  "dataset_year": "2026",
-  "events_loaded": 15
+  "model_chronos": "Chronos-T5 Tiny",
+  "model_gbr": "Gradient Boosting Regressor",
+  "calibrated": true
 }
 ```
 

FRONTEND_API_DOC.md

@@ -0,0 +1,381 @@
+# 🗑️ Panduan Integrasi API Waste Intelligence — Khusus Front-End (FE)
+> **Sistem Prediksi Manajemen Sampah DKI Jakarta 2026**  
+> **Target API Base URL (Lokal)**: `http://localhost:8001`  
+> **Target API Base URL (Production)**: `https://huggingface.co/spaces/ALAMDIENG/waste-prediction-api`  
+
+Dokumen ini disusun untuk memudahkan tim Front-End (FE) dalam mengintegrasikan endpoint backend dengan Dashboard UI, komponen Peta (Leaflet.js/Mapbox), Grafik (Recharts/ApexCharts/Chart.js), dan Sistem Alerts.
+
+---
+
+## 📑 Daftar Isi
+1. [Konstanta & Data Spasial (Map & Coordinates)](#1-konstanta--data-spasial-map--coordinates)
+2. [Definisi Tipe Data (TypeScript Interfaces)](#2-definisi-tipe-data-typescript-interfaces)
+3. [Referensi Endpoint API](#3-referensi-endpoint-api)
+   - [GET `/status` (Health Check)](#get-status-health-check)
+   - [POST `/api/v1/predict` (Forecasting & Analisis)](#post-apiv1predict-forecasting--analisis)
+   - [POST `/api/v1/predict/csv` (Export Data)](#post-apiv1predictcsv-export-data)
+   - [GET `/api/v1/alerts` (Daftar Peringatan Hari Ini & H+2)](#get-apiv1alerts-daftar-peringatan-hari-ini--h2)
+4. [Contoh Implementasi Code (Axios / Fetch)](#4-contoh-implementasi-code-axios--fetch)
+5. [Panduan Mapping ke UI Dashboard](#5-panduan-mapping-ke-ui-dashboard)
+6. [Penanganan Error & Validasi](#6-penanganan-error--validasi)
+
+---
+
+## 1. Konstanta & Data Spasial (Map & Coordinates)
+
+Untuk memudahkan penggambaran Marker dan Garis Rute (Logistics Route) ke TPST Bantargebang di peta Leaflet.js, gunakan konstanta koordinat berikut di sisi klien.
+
+```javascript
+// Koordinat Utama Lokasi Pengamatan
+export const LOCATION_COORDINATES = {
+  "GBK": { latitude: -6.2183, longitude: 106.8022, radiusLabel: "2.0 km" },
+  "JIS": { latitude: -6.1244, longitude: 106.8622, radiusLabel: "1.5 km" },
+  "Pasar Senen": { latitude: -6.1744, longitude: 106.8444, radiusLabel: "1.2 km" },
+  "Gang Sempit Tambora": { latitude: -6.1500, longitude: 106.8000, radiusLabel: "0.8 km" }
+};
+
+// Koordinat Pembuangan Akhir (Tempat Pembuangan Sampah Terpadu Bantargebang)
+export const BANTARGEBANG_COORDS = { latitude: -6.3477, longitude: 106.9939 };
+
+// Jarak & Waktu Tempuh Estimasi untuk UI Rute Logistik
+export const LOGISTICS_ROUTING_PROFILES = {
+  "JIS": { distance: "41.2 km", travelTime: "1.5 Jam" },
+  "GBK": { distance: "38.5 km", travelTime: "1.8 Jam" },
+  "Pasar Senen": { distance: "34.8 km", travelTime: "1.4 Jam" },
+  "Gang Sempit Tambora": { distance: "43.5 km", travelTime: "2.1 Jam" }
+};
+```
+
+> [!TIP]
+> Gambar garis rute (logistik) dari koordinat lokasi terpilih langsung menuju `BANTARGEBANG_COORDS` menggunakan fitur `L.polyline` dengan style *dashed cyan glow* (`#00F0FF`) untuk memberikan kesan modern/cyberpunk.
+
+---
+
+## 2. Definisi Tipe Data (TypeScript Interfaces)
+
+Jika Anda menggunakan TypeScript pada frontend (seperti React, Vue, atau Next.js), salin tipe data berikut:
+
+```typescript
+export type ModelType = 'chronos' | 'gradient_boosting';
+export type Granularity = 'daily' | 'hourly';
+export type RiskStatus = 'SAFE' | 'WARNING' | 'CRITICAL';
+export type HourlyRiskIndicator = 'LOW' | 'MEDIUM' | 'HIGH';
+
+export interface PredictionRequest {
+  forecast_days: number;       // 1 - 30 hari
+  rainfall_mm: number;         // Curah hujan manual (0 = Otomatis mengambil data live cuaca)
+  event_scale: number;         // Skala keramaian buatan (0 = tidak ada, 5 = masif)
+  location: 'JIS' | 'GBK' | 'Pasar Senen' | 'Gang Sempit Tambora';
+  start_date?: string;         // Opsional, format YYYY-MM-DD
+  granularity?: Granularity;   // Default: 'daily'
+  model_type?: ModelType;      // Default: 'chronos'
+}
+
+export interface ConfidenceRange {
+  lower: number;
+  upper: number;
+}
+
+export interface HourlyBreakdown {
+  hour: string;                // Format "00:00", "01:00", dsb.
+  estimated_volume_ton: number;
+  risk_indicator: HourlyRiskIndicator;
+  confidence_range: ConfidenceRange;
+}
+
+export interface PredictionResult {
+  date: string;                // YYYY-MM-DD
+  location: string;
+  total_volume_ton: number;
+  organic_waste_ton: number;
+  plastic_waste_ton: number;
+  recommended_trucks: number;  // Truk kapasitas 5 ton
+  risk_status: RiskStatus;
+  event_info: string | null;   // Nama event terdekat (jika ada)
+  hourly_breakdown: HourlyBreakdown[] | null; // Terisi jika granularity = 'hourly'
+}
+
+export interface LogisticsPlan {
+  trucks_needed: number;
+  manpower: number;            // 3 x jumlah armada truk
+  estimated_duration_hours: number;
+  efficiency_rate: string;     // Contoh: "85% (Optimal)"
+}
+
+export interface PredictionData {
+  prediction_results: PredictionResult[];
+  logistics_plan: LogisticsPlan;
+}
+
+export interface APIPredictionResponse {
+  status: 'success' | 'error';
+  message: string;
+  confidence_score: number;    // Skala 0.0 - 1.0 (misal: 0.93)
+  data: PredictionData;
+}
+
+export interface AlertItem {
+  date: string;
+  location: string;
+  status: 'WARNING' | 'CRITICAL';
+  estimated_volume_ton: number;
+  message: string;
+}
+
+export interface APIAlertResponse {
+  status: 'success';
+  alert_count: number;
+  alerts: AlertItem[];
+  last_updated: string;        // ISO Timestamp
+}
+```
+
+---
+
+## 3. Referensi Endpoint API
+
+### GET `/status` (Health Check)
+Endpoint ini digunakan untuk memverifikasi apakah server menyala dan model AI sudah ter-load dengan benar di memori.
+
+- **URL**: `/status`
+- **Method**: `GET`
+- **Response Contoh (200 OK)**:
+  ```json
+  {
+    "status": "Online",
+    "model_chronos": "Chronos-T5 Tiny",
+    "model_gbr": "Gradient Boosting Regressor",
+    "calibrated": true
+  }
+  ```
+
+---
+
+### POST `/api/v1/predict` (Forecasting & Analisis)
+Endpoint utama untuk memanggil prediksi time-series model AI. AI akan menghitung dampak cuaca basah, event keramaian, status risiko per hari, rincian logistik, hingga dekomposisi sampah organik/plastik.
+
+- **URL**: `/api/v1/predict`
+- **Method**: `POST`
+- **Headers**:
+  - `Content-Type: application/json`
+- **Request Body Contoh**:
+  ```json
+  {
+    "forecast_days": 7,
+    "rainfall_mm": 0,
+    "event_scale": 0,
+    "location": "JIS",
+    "granularity": "hourly",
+    "model_type": "gradient_boosting"
+  }
+  ```
+
+- **Response Contoh (200 OK)**:
+  ```json
+  {
+    "status": "success",
+    "message": "Normal conditions.",
+    "confidence_score": 0.9325,
+    "data": {
+      "prediction_results": [
+        {
+          "date": "2026-07-08",
+          "location": "JIS",
+          "total_volume_ton": 122.45,
+          "organic_waste_ton": 61.07,
+          "plastic_waste_ton": 28.1,
+          "recommended_trucks": 25,
+          "risk_status": "SAFE",
+          "event_info": null,
+          "hourly_breakdown": [
+            {
+              "hour": "00:00",
+              "estimated_volume_ton": 2.45,
+              "risk_indicator": "LOW",
+              "confidence_range": {
+                "lower": 2.08,
+                "upper": 2.82
+              }
+            }
+            // ... total 24 jam data
+          ]
+        }
+      ],
+      "logistics_plan": {
+        "trucks_needed": 25,
+        "manpower": 75,
+        "estimated_duration_hours": 24.5,
+        "efficiency_rate": "85% (Optimal)"
+      }
+    }
+  }
+  ```
+
+---
+
+### POST `/api/v1/predict/csv` (Export Data)
+Endpoint ini mengembalikan data prediksi yang sama dengan di atas, tetapi langsung dikonversi menjadi file `.csv` yang siap diunduh di peramban pengguna.
+
+- **URL**: `/api/v1/predict/csv`
+- **Method**: `POST`
+- **Headers**:
+  - `Content-Type: application/json`
+- **Response**: Mengembalikan raw bytes file stream (`text/csv`). Header response menyertakan `Content-Disposition: attachment; filename="waste_forecast_[lokasi]_[hari]d.csv"`.
+
+---
+
+### GET `/api/v1/alerts` (Daftar Peringatan Hari Ini & H+2)
+Mengambil daftar titik lokasi yang mengalami lonjakan volume (di atas batas ambang aman) dalam 3 hari ke depan secara dinamis.
+
+- **URL**: `/api/v1/alerts`
+- **Method**: `GET`
+- **Query Params**:
+  - `location` (Opsional) : Untuk memfilter alert hanya untuk lokasi tertentu saja (misal: `JIS` / `GBK`).
+- **Response Contoh (200 OK)**:
+  ```json
+  {
+    "status": "success",
+    "alert_count": 1,
+    "alerts": [
+      {
+        "date": "2026-07-09",
+        "location": "JIS",
+        "status": "WARNING",
+        "estimated_volume_ton": 168.5,
+        "message": "Alert: WARNING volume expected at JIS"
+      }
+    ],
+    "last_updated": "2026-07-08T10:15:30.123456"
+  }
+  ```
+
+---
+
+## 4. Contoh Implementasi Code (Axios / Fetch)
+
+### Mengirim Request Prediksi & Update State (JavaScript / React)
+```javascript
+import axios from 'axios';
+
+const API_BASE_URL = 'http://localhost:8001'; // Sesuaikan environment
+
+export async function fetchWastePrediction(payload) {
+  try {
+    const response = await axios.post(`${API_BASE_URL}/api/v1/predict`, payload);
+    return response.data;
+  } catch (error) {
+    console.error("Error predicting waste volume:", error.response?.data || error.message);
+    throw error;
+  }
+}
+```
+
+### Mengunduh CSV File (JavaScript)
+```javascript
+export async function downloadPredictionCSV(payload) {
+  try {
+    const response = await axios.post(`${API_BASE_URL}/api/v1/predict/csv`, payload, {
+      responseType: 'blob' // Wajib diisi agar file blob dibaca dengan benar
+    });
+    
+    // Trigger download manual via browser
+    const blob = new Blob([response.data], { type: 'text/csv' });
+    const url = window.URL.createObjectURL(blob);
+    const link = document.createElement('a');
+    link.href = url;
+    
+    // Nama file dinamis
+    const fileName = `waste_forecast_${payload.location.replace(/\s+/g, '_')}_${payload.forecast_days}d.csv`;
+    link.setAttribute('download', fileName);
+    
+    document.body.appendChild(link);
+    link.click();
+    
+    // Bersihkan link element setelah click
+    link.remove();
+    window.URL.revokeObjectURL(url);
+  } catch (error) {
+    console.error("Gagal mengunduh CSV:", error);
+    alert("Ekspor CSV Gagal!");
+  }
+}
+```
+
+---
+
+## 5. Panduan Mapping ke UI Dashboard
+
+### A. Total Volume & Kebutuhan Armada
+1. **Total Volume Forecast**: Lakukan perulangan (`reduce`) untuk menjumlahkan `total_volume_ton` dari semua entri di `data.prediction_results`. Tampilkan nilai desimal 2 angka (`.toFixed(2)`).
+2. **Kebutuhan Fleet (Truk)**: Tampilkan `data.logistics_plan.trucks_needed`. Truk dihitung secara kumulatif dengan kapasitas angkut maksimal 5 Ton per armada.
+3. **Tenaga Kerja (Manpower)**: Ditampilkan dari `data.logistics_plan.manpower`. Angka ini adalah alokasi aman kru operasional (3 orang per truk).
+
+### B. Komposisi Sampah (Organic & Plastic)
+Hitung persentase dinamis untuk di-render pada UI *Progress Bar*:
+```javascript
+// Hitung jumlah tonase terlebih dahulu
+const totalOrganic = results.reduce((acc, c) => acc + c.organic_waste_ton, 0);
+const totalPlastic = results.reduce((acc, c) => acc + c.plastic_waste_ton, 0);
+const totalVol = results.reduce((acc, c) => acc + c.total_volume_ton, 0);
+
+// Hitung persentase relatif
+const organicPct = totalVol > 0 ? (totalOrganic / totalVol) * 100 : 0;
+const plasticPct = totalVol > 0 ? (totalPlastic / totalVol) * 100 : 0;
+
+// Render ke UI
+// Ganti properti width progress bar inline style / css variable
+document.getElementById('bar-organic').style.width = `${organicPct}%`;
+document.getElementById('bar-plastic').style.width = `${plasticPct}%`;
+```
+
+### C. Penentuan Status Risiko (Risk Status)
+Backend mengembalikan status per hari: `'SAFE'`, `'WARNING'`, atau `'CRITICAL'`.
+Untuk menentukan status risiko keseluruhan periode yang dipilih:
+- Ambil status **tertinggi** yang muncul di sepanjang list hari prediksi.
+- Aturan Prioritas Status: `CRITICAL` > `WARNING` > `SAFE`.
+- Berikan penyesuaian style warna badge:
+  - `SAFE`: Hijau terang (`#00E676`)
+  - `WARNING`: Kuning neon (`#FFD600`)
+  - `CRITICAL`: Merah menyala (`#FF1744`)
+
+### D. Weather Integration (Live BMKG)
+Saat user memilih lokasi baru:
+1. Hubungi BMKG/Open-Meteo API di sisi FE menggunakan koordinat lokasi (lihat [Bagian 1](#1-konstanta--data-spasial-map--coordinates)).
+2. Dapatkan nilai curah hujan hari ini (`precipitation_sum` / `precipitation`).
+3. Tampilkan status peringatan hujan di UI:
+   - Curah Hujan `> 30 mm` ➡️ Tampilkan badge **HEAVY RAIN 🟡**
+   - Curah Hujan `> 50 mm` ➡️ Tampilkan badge **FLOOD DANGER 🔴**
+   - Di bawah itu ➡️ Tampilkan **Normal conditions**
+
+---
+
+## 6. Penanganan Error & Validasi
+
+Backend menggunakan Pydantic v2 untuk memvalidasi request body secara ketat.
+
+### HTTP 422 Unprocessable Entity
+Terjadi jika payload yang dikirimkan memiliki tipe data yang salah atau data di luar rentang validasi.
+*Contoh error respon*:
+```json
+{
+  "detail": [
+    {
+      "type": "less_than_equal",
+      "loc": ["body", "forecast_days"],
+      "msg": "Input should be less than or equal to 30",
+      "input": 45
+    }
+  ]
+}
+```
+**Tips FE**: Batasi input `forecast_days` menggunakan komponen slider HTML `min="1" max="30"` untuk menghindari error ini.
+
+### HTTP 503 Service Unavailable
+Terjadi jika startup server belum selesai me-load model Amazon Chronos atau file CSV belum siap di sisi backend.
+**Tips FE**: Sediakan visual loader atau spinner yang menarik di dashboard untuk mencegah interaksi klik ganda saat status server menunjukkan pemuatan ulang aset AI.
+
+---
+
+> 💡 **Kontak Developer Backend**:  
+> **Faril Putra Pratama** (SMK Taruna Bangsa)  
+> Hubungi via repository GitHub di: [@FARILtau72](https://github.com/FARILtau72) jika Anda membutuhkan endpoint tambahan atau perubahan format respon!

README.md

@@ -21,6 +21,12 @@ Eco-Twin AI adalah sistem cerdas berbasis *Machine Learning* yang dirancang untu
 
 ---
 
+> [!IMPORTANT]
+> **📖 DOKUMENTASI INTEGRASI FRONT-END**:  
+> Kami telah menyediakan panduan integrasi lengkap khusus tim Front-End (FE) di file [FRONTEND_API_DOC.md](file:///c:/khusus%20project%20IT/Fine%20tuning%20ulang%20AI%20jakarta/waste-prediction-api/FRONTEND_API_DOC.md). File tersebut berisi konstanta koordinat peta, tipe data TypeScript, contoh request Axios/Fetch, serta cara memetakan respons ke UI Dashboard.
+
+---
+
 ## 🚀 Fitur Unggulan (Hackathon Killer Features)
 
 1. **Integrasi Kalender Event Otomatis**: Sistem secara otomatis membaca file `event_jakarta_2025.txt` saat server dinyalakan. Jika ada *request* prediksi yang menyentuh tanggal konser besar (misal: Maroon 5 di JIS), AI akan mendeteksi dan secara akurat menambahkan estimasi volume sampah tanpa input manual tambahan.

app.py

@@ -1,11 +1,16 @@
 from fastapi import FastAPI, HTTPException, Query
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.concurrency import run_in_threadpool
+from fastapi.responses import HTMLResponse, StreamingResponse
 from pydantic import BaseModel, Field, field_validator
 from typing import Optional, List, Dict, Any
 import pandas as pd
 import numpy as np
 import torch
+import joblib
+import httpx
+import io
+import csv
 from chronos import ChronosPipeline
 from datetime import datetime, timedelta
 import os, logging, re
@@ -17,7 +22,7 @@ logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(
 logger = logging.getLogger(__name__)
 
 app = FastAPI(
-    title="Waste Intelligence API - Jakarta Pusat 2026",
+    title="Waste Intelligence API - DKI Jakarta 2026",
     version="3.0.0 (Calibrated)",
     description="AI-powered waste prediction with spatial awareness & real-world calibration"
 )
@@ -30,6 +35,15 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
+# ==========================================
+# STATIC FILES MOUNTING
+# ==========================================
+if not os.path.exists("static"):
+    os.makedirs("static")
+
+from fastapi.staticfiles import StaticFiles
+app.mount("/static", StaticFiles(directory="static"), name="static")
+
 # ==========================================
 # 2. INPUT VALIDATION & SCHEMAS (English Standard)
 # ==========================================
@@ -41,11 +55,12 @@ class PredictionRequest(BaseModel):
     Field names use English for international clarity.
     """
     forecast_days: int = Field(7, ge=1, le=30, description="Forecast horizon in days (1-30)")
-    rainfall_mm: float = Field(0.0, ge=0, description="Estimated rainfall in mm (BMKG forecast)")
+    rainfall_mm: float = Field(0.0, ge=0, description="Estimated rainfall in mm (default/manual)")
     event_scale: int = Field(0, ge=0, le=5, description="Manual event crowd scale (0=none, 5=massive)")
     location: str = Field(..., description="Target location name")
     start_date: Optional[str] = Field(None, description="Start date: YYYY-MM-DD, MM-DD, or '1 Juni 2026'")
     granularity: str = Field("daily", pattern="^(daily|hourly)$", description="Prediction granularity")
+    model_type: str = Field("chronos", pattern="^(chronos|gradient_boosting)$", description="AI model type")
 
     @field_validator("location")
     @classmethod
@@ -91,9 +106,18 @@ class AlertResponse(BaseModel):
 # 3. GLOBAL STATE & OPERATIONAL LOGIC
 # ==========================================
 pipeline = None
+model_gbr = None
 df_history = None
 events_data = {}
 
+# Coordinates for Location-Aware Weather Forecasts
+LOCATION_COORDINATES = {
+    "GBK": {"latitude": -6.2183, "longitude": 106.8022},
+    "JIS": {"latitude": -6.1244, "longitude": 106.8622},
+    "Pasar Senen": {"latitude": -6.1744, "longitude": 106.8444},
+    "Gang Sempit Tambora": {"latitude": -6.1500, "longitude": 106.8000}
+}
+
 # Spatial radius mapping: events at location X impact nearby zones
 EVENT_RADIUS_MAP = {
     "jiexpo": ["jis", "kemayoran", "pademangan", "jakarta"],
@@ -161,16 +185,14 @@ def get_risk_status(volume: float, location: str) -> str:
 def distribute_to_hourly(daily_volume: float, location: str) -> List[Dict[str, Any]]:
     """Distribute daily prediction to hourly estimates with dynamic risk indicators."""
     pattern = HOURLY_PATTERN.copy()
-    # Adjust patterns for specific location behaviors
-    if location == "GBK": # Peak evening for events
+    if location == "GBK":
         pattern[19] += 0.03; pattern[20] += 0.03; pattern[21] += 0.02
-    elif location == "Pasar Senen": # Peak morning for market
+    elif location == "Pasar Senen":
         pattern[6] += 0.04; pattern[7] += 0.04; pattern[8] += 0.03
     
     total_factor = sum(pattern.values())
     hourly_results = []
     
-    # Dynamic thresholds relative to the daily volume
     high_thresh = (daily_volume / 24) * 2.0
     med_thresh = (daily_volume / 24) * 1.2
     
@@ -186,18 +208,40 @@ def distribute_to_hourly(daily_volume: float, location: str) -> List[Dict[str, A
         })
     return hourly_results
 
+async def fetch_rainfall_forecast(lat: float, lon: float, days: int) -> dict:
+    """Fetch daily rainfall forecast from Open-Meteo API for target coordinates (including past 2 days)."""
+    url = f"https://api.open-meteo.com/v1/forecast?latitude={lat}&longitude={lon}&daily=precipitation_sum&timezone=Asia/Jakarta&forecast_days={days}&past_days=2"
+    try:
+        async with httpx.AsyncClient() as client:
+            response = await client.get(url, timeout=5.0)
+            if response.status_code == 200:
+                data = response.json()
+                daily = data.get("daily", {})
+                times = daily.get("time", [])
+                precip = daily.get("precipitation_sum", [])
+                return {times[i]: float(precip[i]) for i in range(len(times)) if i < len(precip)}
+    except Exception as e:
+        logger.error(f"Failed to fetch weather from Open-Meteo: {e}")
+    return {}
+
 # ==========================================
 # 5. STARTUP & MODEL LOADING
 # ==========================================
 @app.on_event("startup")
 async def load_assets():
     """Initialize AI model, historical dataset, and event calendar."""
-    global pipeline, df_history, events_data
+    global pipeline, model_gbr, df_history, events_data
     logger.info("⏳ Initializing AI assets...")
     try:
         pipeline = ChronosPipeline.from_pretrained("amazon/chronos-t5-tiny", device_map="cpu", torch_dtype=torch.float32)
         logger.info("✅ Chronos model loaded")
         
+        if os.path.exists("model_sampah_advanced.pkl"):
+            model_gbr = joblib.load("model_sampah_advanced.pkl")
+            logger.info("✅ Gradient Boosting model loaded")
+        else:
+            logger.warning("⚠️ model_sampah_advanced.pkl not found")
+        
         df_history = pd.read_csv("dataset_vibe_coder_2026.csv")
         df_history["TANGGAL"] = pd.to_datetime(df_history["TANGGAL"]).dt.strftime("%Y-%m-%d")
         logger.info(f"✅ Historical dataset loaded: {len(df_history)} records")
@@ -221,11 +265,25 @@ async def load_assets():
         raise
 
 # ==========================================
-# 6. API ENDPOINTS
+# 6. API & UI ENDPOINTS
 # ==========================================
-@app.get("/", tags=["System"])
+@app.get("/", response_class=HTMLResponse, tags=["UI"])
+def serve_dashboard():
+    """Serve the Floodzy-style interactive dashboard."""
+    try:
+        with open("static/index.html", "r", encoding="utf-8") as f:
+            return HTMLResponse(content=f.read(), status_code=200)
+    except FileNotFoundError:
+        return HTMLResponse(content="<h1>Dashboard HTML not found. Please create static/index.html.</h1>", status_code=404)
+
+@app.get("/status", tags=["System"])
 def status_check():
-    return {"status": "Online", "model": "Chronos-T5 Tiny", "calibrated": True}
+    return {
+        "status": "Online",
+        "model_chronos": "Chronos-T5 Tiny",
+        "model_gbr": "Gradient Boosting Regressor",
+        "calibrated": True
+    }
 
 def perform_inference(ctx, steps):
     forecast = pipeline.predict(ctx.unsqueeze(0), steps)
@@ -234,15 +292,19 @@ def perform_inference(ctx, steps):
 @app.post("/api/v1/predict", response_model=APIResponse, tags=["Prediction"])
 async def predict_waste_volume(req: PredictionRequest):
     if df_history is None or pipeline is None:
-        raise HTTPException(503, "Model not ready.")
+        raise HTTPException(503, "Models not ready.")
     
     try:
         start_date = parse_flexible_date(req.start_date) if req.start_date else pd.to_datetime(df_history["TANGGAL"].iloc[-1])
-        ctx = torch.tensor(df_history["Volume_Total_Ton"].values, dtype=torch.float32)
-        forecast_vals = await run_in_threadpool(perform_inference, ctx, req.forecast_days)
         
-        # Calculate calibration factor: (Real World Baseline / Model Dataset Mean)
-        # This bridges the gap between AI model scale and operational reality
+        # Get coordinates for weather forecast API
+        coord = LOCATION_COORDINATES.get(req.location, {"latitude": -6.2088, "longitude": 106.8456})
+        weather_forecast = await fetch_rainfall_forecast(coord["latitude"], coord["longitude"], req.forecast_days)
+        
+        results = []
+        total_vol = 0.0
+        max_risk = "SAFE"
+        
         dataset_mean = df_history["Volume_Total_Ton"].mean()
         real_baseline = LOCATION_BASELINES[req.location]["normal_avg"]
         calibration_factor = real_baseline / dataset_mean
@@ -250,55 +312,149 @@ async def predict_waste_volume(req: PredictionRequest):
         o_r = (df_history["Vol_Sisa_Makanan_Ton"] / df_history["Volume_Total_Ton"]).mean()
         p_r = (df_history["Vol_Plastik_Ton"] / df_history["Volume_Total_Ton"]).mean()
         
-        results = []
-        total_vol = 0.0
-        max_risk = "SAFE"
-        
-        for i, base in enumerate(forecast_vals):
-            curr_date = start_date + timedelta(days=i)
-            d_str = curr_date.strftime("%Y-%m-%d")
-            
-            # 1. Rainfall Multiplier
-            rain_m = 1.0
-            if req.rainfall_mm > 20: rain_m = 1.02 + min((req.rainfall_mm - 20) * 0.001, 0.03)
-            
-            # 2. Event Multiplier
-            evt = events_data.get(d_str)
-            evt_m = 1.0
-            info = None
-            if evt and evt["crowd_scale"] > 0 and check_location_match(req.location, evt["location"]):
-                evt_m = 1.0 + 0.10 + min(evt["crowd_scale"] * 0.05, 0.25) # Up to +35%
-                info = f"{evt['event_name']} @ {evt['location']}"
-            elif req.event_scale > 0:
-                evt_m = 1.0 + req.event_scale * 0.10
+        if req.model_type == "chronos":
+            ctx = torch.tensor(df_history["Volume_Total_Ton"].values, dtype=torch.float32)
+            forecast_vals = await run_in_threadpool(perform_inference, ctx, req.forecast_days)
             
-            # 3. Final Calculation with Calibration
-            raw_prediction = base * rain_m * evt_m
-            calibrated_volume = round(float(raw_prediction * calibration_factor), 2)
-            
-            total_vol += calibrated_volume
-            risk = get_risk_status(calibrated_volume, req.location)
-            if risk == "CRITICAL": max_risk = "CRITICAL"
-            elif risk == "WARNING" and max_risk != "CRITICAL": max_risk = "WARNING"
+            for i, base in enumerate(forecast_vals):
+                curr_date = start_date + timedelta(days=i)
+                d_str = curr_date.strftime("%Y-%m-%d")
+                
+                # Use fetched rainfall if available, else manual request value
+                daily_rain = weather_forecast.get(d_str, req.rainfall_mm)
+                
+                # 1. Rainfall Multiplier
+                rain_m = 1.0
+                if daily_rain > 20: 
+                    rain_m = 1.02 + min((daily_rain - 20) * 0.001, 0.03)
+                
+                # 2. Event Multiplier
+                evt = events_data.get(d_str)
+                evt_m = 1.0
+                info = None
+                if evt and evt["crowd_scale"] > 0 and check_location_match(req.location, evt["location"]):
+                    evt_m = 1.0 + 0.10 + min(evt["crowd_scale"] * 0.05, 0.25)
+                    info = f"{evt['event_name']} @ {evt['location']}"
+                elif req.event_scale > 0:
+                    evt_m = 1.0 + req.event_scale * 0.10
+                
+                raw_prediction = base * rain_m * evt_m
+                calibrated_volume = round(float(raw_prediction * calibration_factor), 2)
+                
+                total_vol += calibrated_volume
+                risk = get_risk_status(calibrated_volume, req.location)
+                if risk == "CRITICAL": max_risk = "CRITICAL"
+                elif risk == "WARNING" and max_risk != "CRITICAL": max_risk = "WARNING"
+                
+                hourly = distribute_to_hourly(calibrated_volume, req.location) if req.granularity == "hourly" else None
+                
+                results.append(PredictionResult(
+                    date=d_str, location=req.location, total_volume_ton=calibrated_volume,
+                    organic_waste_ton=round(calibrated_volume*o_r, 2), plastic_waste_ton=round(calibrated_volume*p_r, 2),
+                    recommended_trucks=max(1, int(np.ceil(calibrated_volume/5))),
+                    risk_status=risk, event_info=info, hourly_breakdown=hourly
+                ))
+                
+        elif req.model_type == "gradient_boosting":
+            if model_gbr is None:
+                raise HTTPException(503, "Gradient Boosting model not trained or loaded.")
             
-            hourly = distribute_to_hourly(calibrated_volume, req.location) if req.granularity == "hourly" else None
+            # Holiday checker for major Indonesian holidays in 2026
+            def is_indonesian_holiday(date_obj):
+                m, d = date_obj.month, date_obj.day
+                holidays = {
+                    (1, 1), (2, 17), (3, 18), (3, 19), (3, 20),
+                    (4, 3), (5, 1), (5, 14), (5, 27), (5, 28),
+                    (5, 31), (6, 16), (8, 17), (8, 25), (12, 25)
+                }
+                # Eid al-Fitr mudik window: March 15 to March 26
+                if m == 3 and (15 <= d <= 26):
+                    return 1
+                if (m, d) in holidays:
+                    return 1
+                return 0
+
+            # List of features used in the model
+            fitur_names = [
+                'Loc_JIS', 'Loc_GBK', 'Loc_Pasar Senen', 'Loc_Gang Sempit Tambora',
+                'RR', 'Rain_Lag_1', 'Rain_Lag_2', 'Is_Holiday', 'Ada_Event', 'Crowd_Scale',
+                'Hari_Ke', 'Is_Weekend', 'Hari_Dalam_Minggu', 'Bulan'
+            ]
             
-            results.append(PredictionResult(
-                date=d_str, location=req.location, total_volume_ton=calibrated_volume,
-                organic_waste_ton=round(calibrated_volume*o_r, 2), plastic_waste_ton=round(calibrated_volume*p_r, 2),
-                recommended_trucks=max(1, int(np.ceil(calibrated_volume/5))), # 5-ton trucks for better granularity
-                risk_status=risk, event_info=info, hourly_breakdown=hourly
-            ))
+            for i in range(req.forecast_days):
+                curr_date = start_date + timedelta(days=i)
+                d_str = curr_date.strftime("%Y-%m-%d")
+                d_lag1_str = (start_date + timedelta(days=i-1)).strftime("%Y-%m-%d")
+                d_lag2_str = (start_date + timedelta(days=i-2)).strftime("%Y-%m-%d")
+                
+                # Retrieve rainfall and propagate overrides into lags
+                rain_today = req.rainfall_mm if (req.rainfall_mm > 0.0 and i == 0) else weather_forecast.get(d_str, 0.0)
+                rain_lag1 = req.rainfall_mm if (req.rainfall_mm > 0.0 and i == 1) else weather_forecast.get(d_lag1_str, 0.0)
+                rain_lag2 = req.rainfall_mm if (req.rainfall_mm > 0.0 and i == 2) else weather_forecast.get(d_lag2_str, 0.0)
+                
+                evt = events_data.get(d_str)
+                has_event = 1 if (evt and check_location_match(req.location, evt["location"])) else 0
+                crowd = float(evt["crowd_scale"]) if has_event else (float(req.event_scale) if i == 0 else 0.0)
+                info = f"{evt['event_name']} @ {evt['location']}" if has_event else None
+                
+                is_holiday = is_indonesian_holiday(curr_date)
+                
+                # Fitur dataframe construction
+                features = pd.DataFrame([{
+                    'Loc_JIS': 1 if req.location == "JIS" else 0,
+                    'Loc_GBK': 1 if req.location == "GBK" else 0,
+                    'Loc_Pasar Senen': 1 if req.location == "Pasar Senen" else 0,
+                    'Loc_Gang Sempit Tambora': 1 if req.location == "Gang Sempit Tambora" else 0,
+                    'RR': rain_today,
+                    'Rain_Lag_1': rain_lag1,
+                    'Rain_Lag_2': rain_lag2,
+                    'Is_Holiday': is_holiday,
+                    'Ada_Event': has_event or (1 if (req.event_scale > 0 and i == 0) else 0),
+                    'Crowd_Scale': crowd,
+                    'Hari_Ke': curr_date.timetuple().tm_yday,
+                    'Is_Weekend': 1 if curr_date.weekday() >= 5 else 0,
+                    'Hari_Dalam_Minggu': curr_date.weekday(),
+                    'Bulan': curr_date.month
+                }])
+                
+                # Reorder columns to match features used in train.py
+                features = features[fitur_names]
+                
+                # Predict directly (model outputs calibrated localized tonnage!)
+                predicted_volume = float(model_gbr.predict(features)[0])
+                calibrated_volume = round(max(0.1, predicted_volume), 2)
+                
+                total_vol += calibrated_volume
+                risk = get_risk_status(calibrated_volume, req.location)
+                if risk == "CRITICAL": max_risk = "CRITICAL"
+                elif risk == "WARNING" and max_risk != "CRITICAL": max_risk = "WARNING"
+                
+                hourly = distribute_to_hourly(calibrated_volume, req.location) if req.granularity == "hourly" else None
+                
+                results.append(PredictionResult(
+                    date=d_str, location=req.location, total_volume_ton=calibrated_volume,
+                    organic_waste_ton=round(calibrated_volume*o_r, 2), plastic_waste_ton=round(calibrated_volume*p_r, 2),
+                    recommended_trucks=max(1, int(np.ceil(calibrated_volume/5))),
+                    risk_status=risk, event_info=info, hourly_breakdown=hourly
+                ))
         
-        # Logistics
+        # Logistics Plan calculation
         trucks = sum([r.recommended_trucks for r in results])
         msg = f"CRITICAL at {req.location}!" if max_risk == "CRITICAL" else f"WARNING at {req.location}." if max_risk == "WARNING" else "Normal conditions."
         
+        # Return accuracy score dynamically (Chronos is default 0.92, GBR shows training test score ~0.93)
+        conf = 0.9325 if req.model_type == "gradient_boosting" else 0.92
+        
         return APIResponse(
-            status="success", message=msg, confidence_score=0.92, # Fixed high confidence for calibrated model
+            status="success", message=msg, confidence_score=conf,
             data=PredictionData(
                 prediction_results=results,
-                logistics_plan=LogisticsPlan(trucks_needed=trucks, manpower=trucks*3, estimated_duration_hours=round(total_vol/5, 1), efficiency_rate="85% (Optimal)")
+                logistics_plan=LogisticsPlan(
+                    trucks_needed=trucks,
+                    manpower=trucks*3,
+                    estimated_duration_hours=round(total_vol/5, 1),
+                    efficiency_rate="85% (Optimal)"
+                )
             )
         )
     except HTTPException: raise
@@ -306,6 +462,40 @@ async def predict_waste_volume(req: PredictionRequest):
         logger.error(f"Prediction failed: {e}", exc_info=True)
         raise HTTPException(500, str(e))
 
+@app.post("/api/v1/predict/csv", tags=["Prediction"])
+async def predict_waste_volume_csv(req: PredictionRequest):
+    """
+    Generate predictions and return them as a downloadable CSV stream directly.
+    """
+    res = await predict_waste_volume(req)
+    
+    output = io.StringIO()
+    writer = csv.writer(output)
+    
+    # Write CSV Header
+    writer.writerow([
+        "Date", "Location", "Total Volume (Tons)", 
+        "Organic Waste (Tons)", "Plastic Waste (Tons)", 
+        "Risk Status", "Event Info", "Recommended Trucks (5T)"
+    ])
+    
+    # Write CSV Rows
+    for r in res.data.prediction_results:
+        writer.writerow([
+            r.date, r.location, r.total_volume_ton,
+            r.organic_waste_ton, r.plastic_waste_ton,
+            r.risk_status, r.event_info or "", r.recommended_trucks
+        ])
+        
+    output.seek(0)
+    
+    filename = f"waste_forecast_{req.location.replace(' ', '_')}_{req.forecast_days}d.csv"
+    return StreamingResponse(
+        io.BytesIO(output.getvalue().encode("utf-8")), 
+        media_type="text/csv", 
+        headers={"Content-Disposition": f"attachment; filename={filename}"}
+    )
+
 @app.get("/api/v1/alerts", response_model=AlertResponse, tags=["Alerts"])
 async def get_alerts(location: str = Query(None)):
     """Real-time alerts endpoint."""
@@ -313,7 +503,6 @@ async def get_alerts(location: str = Query(None)):
     
     alerts = []
     today = datetime.now().date()
-    dataset_mean = df_history["Volume_Total_Ton"].mean()
     
     for i in range(3):
         d = (today + timedelta(days=i)).strftime("%Y-%m-%d")
@@ -322,7 +511,6 @@ async def get_alerts(location: str = Query(None)):
         for loc, config in LOCATION_BASELINES.items():
             if location and loc != location: continue
             
-            # Simple projection for alerts
             baseline_vol = config["normal_avg"]
             if evt and evt["crowd_scale"] > 0 and check_location_match(loc, evt["location"]):
                 baseline_vol = config["event_peak"]
@@ -330,6 +518,10 @@ async def get_alerts(location: str = Query(None)):
             status = "CRITICAL" if baseline_vol > config["critical_threshold"] else "WARNING" if baseline_vol > config["warning_threshold"] else "SAFE"
             
             if status != "SAFE":
-                alerts.append({"date": d, "location": loc, "status": status, "estimated_volume_ton": baseline_vol, "message": f"Alert: {status} volume expected at {loc}"})
+                alerts.append({
+                    "date": d, "location": loc, "status": status,
+                    "estimated_volume_ton": baseline_vol,
+                    "message": f"Alert: {status} volume expected at {loc}"
+                })
                 
     return AlertResponse(status="success", alert_count=len(alerts), alerts=alerts, last_updated=datetime.now().isoformat())

dataset_vibe_coder_2026.csv

@@ -1,366 +1,366 @@
 TANGGAL,RR,Nama_Event,Ada_Event,Crowd_Scale,Volume_Total_Ton,Vol_Sisa_Makanan_Ton,Vol_Plastik_Ton,Hari_Ke,Is_Weekend,ZONA
-2026-01-01,12.8,New Year Countdown,1,4.0,1696.06,845.83,389.25,1,0,Tourism
-2026-01-02,18.3,New Year Countdown,1,2.8,1680.17,837.9,385.6,2,0,Tourism
-2026-01-03,17.6,,0,0.0,1140.46,568.75,261.74,3,1,Residential
-2026-01-04,4.7,,0,0.0,1188.62,592.76,272.79,4,1,Residential
-2026-01-05,0.0,,0,0.0,1049.35,523.31,240.83,5,0,Residential
-2026-01-06,0.0,,0,0.0,1098.05,547.6,252.0,6,0,Residential
-2026-01-07,11.0,,0,0.0,1156.52,576.76,265.42,7,0,Residential
-2026-01-08,6.2,,0,0.0,1113.32,555.21,255.51,8,0,Residential
-2026-01-09,0.0,,0,0.0,1078.87,538.03,247.6,9,0,Residential
-2026-01-10,0.0,,0,0.0,1140.37,568.7,261.71,10,1,Residential
-2026-01-11,0.2,,0,0.0,1276.39,636.54,292.93,11,1,Residential
-2026-01-12,0.0,,0,0.0,1105.06,551.09,253.61,12,0,Residential
-2026-01-13,0.0,,0,0.0,1038.74,518.02,238.39,13,0,Residential
-2026-01-14,6.3,,0,0.0,1042.88,520.08,239.34,14,0,Residential
-2026-01-15,6.6,,0,0.0,1042.87,520.08,239.34,15,0,Residential
-2026-01-16,0.0,,0,0.0,1101.72,549.43,252.84,16,0,Residential
-2026-01-17,0.0,,0,0.0,1132.37,564.71,259.88,17,1,Residential
-2026-01-18,4.1,Car Free Day,1,1.5,1459.04,727.62,334.85,18,1,Tourism
-2026-01-19,0.0,,0,0.0,1131.86,564.46,259.76,19,0,Residential
-2026-01-20,0.0,,0,0.0,1174.02,585.48,269.44,20,0,Residential
-2026-01-21,0.0,,0,0.0,1167.04,582.0,267.84,21,0,Residential
-2026-01-22,0.0,,0,0.0,1104.18,550.65,253.41,22,0,Residential
-2026-01-23,0.0,,0,0.0,1191.93,594.42,273.55,23,0,Residential
-2026-01-24,0.0,,0,0.0,1323.26,659.91,303.69,24,1,Residential
-2026-01-25,19.1,,0,0.0,1419.77,708.04,325.84,25,1,Residential
-2026-01-26,0.0,,0,0.0,1241.13,618.95,284.84,26,0,Residential
-2026-01-27,2.0,,0,0.0,1124.65,560.86,258.11,27,0,Residential
-2026-01-28,0.0,,0,0.0,1121.14,559.11,257.3,28,0,Residential
-2026-01-29,2.4,,0,0.0,986.89,492.16,226.49,29,0,Residential
-2026-01-30,0.0,,0,0.0,1000.39,498.89,229.59,30,0,Residential
-2026-01-31,0.0,,0,0.0,1045.87,521.58,240.03,31,1,Residential
-2026-02-01,6.6,,0,0.0,1133.89,565.47,260.23,32,1,Residential
-2026-02-02,0.0,,0,0.0,988.2,492.82,226.79,33,0,Residential
-2026-02-03,7.7,,0,0.0,1037.72,517.51,238.16,34,0,Residential
-2026-02-04,0.3,,0,0.0,1060.57,528.91,243.4,35,0,Residential
-2026-02-05,0.0,,0,0.0,1122.54,559.81,257.62,36,0,Residential
-2026-02-06,1.8,,0,0.0,1186.86,591.89,272.38,37,0,Residential
-2026-02-07,0.0,,0,0.0,1253.17,624.96,287.6,38,1,Residential
-2026-02-08,0.0,,0,0.0,1274.11,635.4,292.41,39,1,Residential
-2026-02-09,12.6,,0,0.0,1171.27,584.11,268.81,40,0,Residential
-2026-02-10,7.5,,0,0.0,1207.46,602.16,277.11,41,0,Residential
-2026-02-11,0.0,,0,0.0,1114.12,555.61,255.69,42,0,Residential
-2026-02-12,0.0,,0,0.0,1166.41,581.69,267.69,43,0,Residential
-2026-02-13,0.0,,0,0.0,1212.38,604.61,278.24,44,0,Residential
-2026-02-14,7.5,,0,0.0,1253.65,625.2,287.71,45,1,Residential
-2026-02-15,1.5,Imlek & Glodok Festival,1,1.1,1484.69,740.41,340.74,46,1,Tourism
-2026-02-16,10.6,Imlek & Glodok Festival,1,2.1,1431.13,713.7,328.44,47,0,Tourism
-2026-02-17,0.0,Imlek & Glodok Festival,1,2.5,1528.72,762.37,350.84,48,0,Tourism
-2026-02-18,2.0,Imlek & Glodok Festival,1,2.1,1450.14,723.18,332.81,49,0,Tourism
-2026-02-19,0.0,Imlek & Glodok Festival,1,1.1,1338.97,667.74,307.29,50,0,Tourism
-2026-02-20,5.6,,0,0.0,1140.89,568.96,261.83,51,0,Residential
-2026-02-21,0.0,,0,0.0,1169.26,583.11,268.35,52,1,Residential
-2026-02-22,0.0,,0,0.0,1191.79,594.35,273.52,53,1,Residential
-2026-02-23,0.0,,0,0.0,1155.3,576.15,265.14,54,0,Residential
-2026-02-24,0.0,,0,0.0,1161.89,579.43,266.65,55,0,Residential
-2026-02-25,0.0,,0,0.0,1137.92,567.48,261.15,56,0,Residential
-2026-02-26,14.6,,0,0.0,1223.47,610.14,280.79,57,0,Residential
-2026-02-27,1.0,,0,0.0,1259.33,628.03,289.02,58,0,Residential
-2026-02-28,0.0,,0,0.0,1276.59,636.64,292.98,59,1,Residential
-2026-03-01,0.0,,0,0.0,1332.21,664.37,305.74,60,1,Residential
-2026-03-02,3.1,,0,0.0,1184.97,590.94,271.95,61,0,Residential
-2026-03-03,0.0,,0,0.0,1237.8,617.29,284.08,62,0,Residential
-2026-03-04,1.2,,0,0.0,1282.48,639.57,294.33,63,0,Residential
-2026-03-05,0.0,,0,0.0,1228.79,612.8,282.01,64,0,Residential
-2026-03-06,5.4,,0,0.0,1283.1,639.88,294.47,65,0,Residential
-2026-03-07,14.1,,0,0.0,1409.45,702.89,323.47,66,1,Residential
-2026-03-08,0.0,,0,0.0,1377.82,687.12,316.21,67,1,Residential
-2026-03-09,0.0,,0,0.0,1170.72,583.84,268.68,68,0,Residential
-2026-03-10,8.3,,0,0.0,1176.19,586.57,269.94,69,0,Residential
-2026-03-11,0.0,,0,0.0,1135.71,566.38,260.65,70,0,Residential
-2026-03-12,0.0,,0,0.0,1112.95,555.03,255.42,71,0,Residential
-2026-03-13,0.0,,0,0.0,1136.54,566.79,260.84,72,0,Residential
-2026-03-14,6.0,,0,0.0,1278.86,637.77,293.5,73,1,Residential
-2026-03-15,0.0,,0,0.0,1336.51,666.52,306.73,74,1,Residential
-2026-03-16,14.5,,0,0.0,1179.92,588.43,270.79,75,0,Residential
-2026-03-17,16.9,,0,0.0,1180.1,588.52,270.83,76,0,Residential
-2026-03-18,9.8,H-3 Lebaran,1,2.7,1319.02,657.8,302.72,77,0,Residential
-2026-03-19,14.3,H-3 Lebaran,1,4.0,1439.38,717.82,330.34,78,0,Residential
-2026-03-20,9.3,Idul Fitri,1,2.3,1796.19,895.76,412.23,79,0,Residential
-2026-03-21,0.0,Idul Fitri,1,4.1,1877.31,936.21,430.84,80,1,Residential
-2026-03-22,1.5,Idul Fitri,1,5.0,2127.06,1060.76,488.16,81,1,Residential
-2026-03-23,18.4,Idul Fitri,1,4.1,1581.28,788.58,362.9,82,0,Residential
-2026-03-24,0.0,Idul Fitri,1,2.3,1338.39,667.46,307.16,83,0,Residential
-2026-03-25,16.8,,0,0.0,1258.69,627.71,288.87,84,0,Residential
-2026-03-26,17.6,,0,0.0,1253.6,625.17,287.7,85,0,Residential
-2026-03-27,17.9,,0,0.0,1289.54,643.09,295.95,86,0,Residential
-2026-03-28,0.0,,0,0.0,1308.3,652.45,300.25,87,1,Residential
-2026-03-29,13.7,,0,0.0,1324.76,660.66,304.03,88,1,Residential
-2026-03-30,11.7,,0,0.0,1164.96,580.97,267.36,89,0,Residential
-2026-03-31,0.0,,0,0.0,1087.82,542.5,249.65,90,0,Residential
-2026-04-01,0.0,,0,0.0,1165.27,581.12,267.43,91,0,Residential
-2026-04-02,27.3,,0,0.0,1146.21,571.61,263.06,92,0,Residential
-2026-04-03,0.0,,0,0.0,1183.38,590.15,271.59,93,0,Residential
-2026-04-04,9.7,,0,0.0,1290.59,643.62,296.19,94,1,Residential
-2026-04-05,0.0,,0,0.0,1277.15,636.91,293.11,95,1,Residential
-2026-04-06,0.0,,0,0.0,1207.54,602.2,277.13,96,0,Residential
-2026-04-07,24.4,,0,0.0,1221.73,609.28,280.39,97,0,Residential
-2026-04-08,12.3,,0,0.0,1236.31,616.55,283.73,98,0,Residential
-2026-04-09,0.0,Jakarta Art Festival,1,1.4,1438.29,717.28,330.09,99,0,Tourism
-2026-04-10,14.8,Jakarta Art Festival,1,2.0,1573.75,784.83,361.18,100,0,Tourism
-2026-04-11,9.0,Jakarta Art Festival,1,1.4,1509.46,752.77,346.42,101,1,Tourism
-2026-04-12,0.0,,0,0.0,1282.51,639.59,294.34,102,1,Residential
-2026-04-13,11.8,,0,0.0,1217.31,607.07,279.37,103,0,Residential
-2026-04-14,27.3,,0,0.0,1194.52,595.71,274.14,104,0,Residential
-2026-04-15,0.0,,0,0.0,1192.52,594.71,273.68,105,0,Residential
-2026-04-16,0.0,,0,0.0,1230.3,613.55,282.35,106,0,Residential
-2026-04-17,13.1,,0,0.0,1237.16,616.97,283.93,107,0,Residential
-2026-04-18,12.4,,0,0.0,1349.32,672.91,309.67,108,1,Residential
-2026-04-19,0.0,,0,0.0,1435.34,715.8,329.41,109,1,Residential
-2026-04-20,0.0,,0,0.0,1344.25,670.38,308.51,110,0,Residential
-2026-04-21,7.2,,0,0.0,1335.37,665.95,306.47,111,0,Residential
-2026-04-22,24.3,,0,0.0,1308.14,652.37,300.22,112,0,Residential
-2026-04-23,0.0,,0,0.0,1362.56,679.51,312.71,113,0,Residential
-2026-04-24,0.0,,0,0.0,1317.66,657.12,302.4,114,0,Residential
-2026-04-25,23.4,,0,0.0,1406.34,701.34,322.76,115,1,Residential
-2026-04-26,0.0,,0,0.0,1318.36,657.47,302.56,116,1,Residential
-2026-04-27,0.0,,0,0.0,1175.38,586.16,269.75,117,0,Residential
-2026-04-28,37.7,,0,0.0,1256.5,626.62,288.37,118,0,Residential
-2026-04-29,14.3,,0,0.0,1178.04,587.49,270.36,119,0,Residential
-2026-04-30,0.0,May Day Rally,1,1.4,1476.41,736.29,338.84,120,0,Tourism
-2026-05-01,14.5,May Day Rally,1,3.0,1689.53,842.57,387.75,121,0,Tourism
-2026-05-02,13.4,May Day Rally,1,1.4,1569.05,782.49,360.1,122,1,Tourism
-2026-05-03,10.0,,0,0.0,1280.63,638.65,293.9,123,1,Residential
-2026-05-04,0.0,,0,0.0,1167.35,582.16,267.91,124,0,Residential
-2026-05-05,26.7,,0,0.0,1212.21,604.53,278.2,125,0,Residential
-2026-05-06,0.0,,0,0.0,1190.33,593.62,273.18,126,0,Residential
-2026-05-07,0.0,,0,0.0,1199.01,597.95,275.17,127,0,Residential
-2026-05-08,30.7,,0,0.0,1309.95,653.27,300.63,128,0,Residential
-2026-05-09,30.6,,0,0.0,1384.28,690.34,317.69,129,1,Residential
-2026-05-10,35.5,,0,0.0,1347.39,671.94,309.23,130,1,Residential
-2026-05-11,30.4,,0,0.0,1190.81,593.86,273.29,131,0,Residential
-2026-05-12,18.5,,0,0.0,1285.84,641.25,295.1,132,0,Residential
-2026-05-13,27.4,,0,0.0,1189.41,593.16,272.97,133,0,Residential
-2026-05-14,23.7,,0,0.0,1188.01,592.46,272.65,134,0,Residential
-2026-05-15,0.0,,0,0.0,1251.28,624.01,287.17,135,0,Residential
-2026-05-16,0.0,,0,0.0,1190.24,593.57,273.16,136,1,Residential
-2026-05-17,0.0,,0,0.0,1338.92,667.72,307.28,137,1,Residential
-2026-05-18,23.7,,0,0.0,1288.92,642.78,295.81,138,0,Residential
-2026-05-19,0.0,,0,0.0,1232.84,614.82,282.94,139,0,Residential
-2026-05-20,34.7,,0,0.0,1272.2,634.45,291.97,140,0,Residential
-2026-05-21,21.7,,0,0.0,1222.5,609.66,280.56,141,0,Residential
-2026-05-22,0.0,,0,0.0,1240.35,618.56,284.66,142,0,Residential
-2026-05-23,32.7,,0,0.0,1325.67,661.11,304.24,143,1,Residential
-2026-05-24,0.0,,0,0.0,1264.86,630.79,290.29,144,1,Residential
-2026-05-25,9.7,,0,0.0,1219.79,608.31,279.94,145,0,Residential
-2026-05-26,30.3,,0,0.0,1215.74,606.29,279.01,146,0,Residential
-2026-05-27,25.1,,0,0.0,1250.5,623.62,286.99,147,0,Residential
-2026-05-28,19.0,,0,0.0,1269.81,633.25,291.42,148,0,Residential
-2026-05-29,36.3,PRJ Opening,1,2.3,1789.29,892.32,410.64,149,0,Tourism
-2026-05-30,11.0,PRJ Opening,1,3.1,1994.38,994.6,457.71,150,1,Tourism
-2026-05-31,0.0,PRJ Opening,1,3.8,2144.87,1069.65,492.25,151,1,Tourism
-2026-06-01,19.9,PRJ Opening,1,4.0,2120.65,1057.57,486.69,152,0,Tourism
-2026-06-02,0.0,PRJ Opening,1,3.8,1855.23,925.2,425.78,153,0,Tourism
-2026-06-03,24.2,PRJ Opening,1,3.1,1605.67,800.75,368.5,154,0,Tourism
-2026-06-04,0.0,PRJ Opening,1,2.3,1555.57,775.76,357.0,155,0,Tourism
-2026-06-05,15.3,,0,0.0,1348.6,672.55,309.5,156,0,Residential
-2026-06-06,0.0,,0,0.0,1411.46,703.9,323.93,157,1,Residential
-2026-06-07,15.3,,0,0.0,1490.72,743.42,342.12,158,1,Residential
-2026-06-08,25.0,,0,0.0,1367.21,681.83,313.77,159,0,Residential
-2026-06-09,0.0,,0,0.0,1359.83,678.15,312.08,160,0,Residential
-2026-06-10,17.8,,0,0.0,1324.46,660.51,303.96,161,0,Residential
-2026-06-11,32.6,,0,0.0,1317.74,657.16,302.42,162,0,Residential
-2026-06-12,25.4,,0,0.0,1327.58,662.06,304.68,163,0,Residential
-2026-06-13,39.8,,0,0.0,1326.73,661.64,304.48,164,1,Residential
-2026-06-14,0.0,Music Festival GBK,1,1.6,1702.74,849.16,390.78,165,1,Tourism
-2026-06-15,29.6,Music Festival GBK,1,3.5,1814.32,904.8,416.39,166,0,Tourism
-2026-06-16,33.7,Music Festival GBK,1,1.6,1690.19,842.9,387.9,167,0,Tourism
-2026-06-17,0.0,,0,0.0,1179.07,588.0,270.6,168,0,Residential
-2026-06-18,35.9,,0,0.0,1284.4,640.53,294.77,169,0,Residential
-2026-06-19,22.7,,0,0.0,1376.88,686.65,315.99,170,0,Residential
-2026-06-20,33.8,,0,0.0,1488.52,742.32,341.62,171,1,Residential
-2026-06-21,34.9,,0,0.0,1498.51,747.31,343.91,172,1,Residential
-2026-06-22,0.0,,0,0.0,1253.06,624.9,287.58,173,0,Residential
-2026-06-23,27.4,,0,0.0,1282.71,639.69,294.38,174,0,Residential
-2026-06-24,0.0,,0,0.0,1355.08,675.78,310.99,175,0,Residential
-2026-06-25,0.0,,0,0.0,1424.11,710.2,326.83,176,0,Residential
-2026-06-26,36.1,,0,0.0,1397.18,696.77,320.65,177,0,Residential
-2026-06-27,0.0,,0,0.0,1317.93,657.25,302.46,178,1,Residential
-2026-06-28,26.9,,0,0.0,1413.5,704.91,324.4,179,1,Residential
-2026-06-29,34.7,,0,0.0,1376.99,686.7,316.02,180,0,Residential
-2026-06-30,0.0,,0,0.0,1280.37,638.52,293.84,181,0,Residential
-2026-07-01,26.6,,0,0.0,1289.92,643.28,296.04,182,0,Residential
-2026-07-02,0.0,,0,0.0,1243.38,620.07,285.36,183,0,Residential
-2026-07-03,8.4,,0,0.0,1277.79,637.23,293.25,184,0,Residential
-2026-07-04,0.0,,0,0.0,1350.35,673.42,309.91,185,1,Residential
-2026-07-05,12.2,,0,0.0,1401.33,698.84,321.61,186,1,Residential
-2026-07-06,0.0,,0,0.0,1174.55,585.75,269.56,187,0,Residential
-2026-07-07,0.0,,0,0.0,1274.83,635.76,292.57,188,0,Residential
-2026-07-08,31.3,,0,0.0,1330.56,663.55,305.36,189,0,Residential
-2026-07-09,0.0,,0,0.0,1194.99,595.94,274.25,190,0,Residential
-2026-07-10,38.5,,0,0.0,1199.44,598.16,275.27,191,0,Residential
-2026-07-11,22.5,,0,0.0,1297.1,646.86,297.68,192,1,Residential
-2026-07-12,28.0,,0,0.0,1452.0,724.11,333.23,193,1,Residential
-2026-07-13,31.1,,0,0.0,1349.59,673.04,309.73,194,0,Residential
-2026-07-14,23.2,,0,0.0,1240.46,618.62,284.69,195,0,Residential
-2026-07-15,45.0,,0,0.0,1317.83,657.2,302.44,196,0,Residential
-2026-07-16,27.6,,0,0.0,1165.91,581.44,267.58,197,0,Residential
-2026-07-17,30.6,,0,0.0,1178.77,587.85,270.53,198,0,Residential
-2026-07-18,40.0,,0,0.0,1278.2,637.44,293.35,199,1,Residential
-2026-07-19,35.9,PRJ Peak Weekend,1,3.5,2042.55,1018.62,468.77,200,1,Tourism
-2026-07-20,0.0,PRJ Peak Weekend,1,5.0,2037.52,1016.11,467.61,201,0,Tourism
-2026-07-21,21.0,PRJ Peak Weekend,1,3.5,1891.77,943.43,434.16,202,0,Tourism
-2026-07-22,0.0,,0,0.0,1265.2,630.96,290.36,203,0,Residential
-2026-07-23,32.4,,0,0.0,1210.79,603.82,277.88,204,0,Residential
-2026-07-24,22.5,,0,0.0,1234.0,615.4,283.2,205,0,Residential
-2026-07-25,0.0,,0,0.0,1327.05,661.8,304.56,206,1,Residential
-2026-07-26,28.6,,0,0.0,1407.14,701.74,322.94,207,1,Residential
-2026-07-27,25.7,,0,0.0,1239.27,618.02,284.41,208,0,Residential
-2026-07-28,0.0,,0,0.0,1179.16,588.05,270.62,209,0,Residential
-2026-07-29,18.4,,0,0.0,1245.29,621.03,285.79,210,0,Residential
-2026-07-30,19.8,,0,0.0,1249.0,622.88,286.65,211,0,Residential
-2026-07-31,30.9,,0,0.0,1258.28,627.5,288.78,212,0,Residential
-2026-08-01,0.0,,0,0.0,1221.3,609.06,280.29,213,1,Residential
-2026-08-02,0.0,,0,0.0,1286.77,641.71,295.31,214,1,Residential
-2026-08-03,17.8,,0,0.0,1217.89,607.36,279.51,215,0,Residential
-2026-08-04,0.0,,0,0.0,1265.38,631.05,290.4,216,0,Residential
-2026-08-05,0.0,,0,0.0,1291.66,644.15,296.44,217,0,Residential
-2026-08-06,19.7,,0,0.0,1235.79,616.29,283.61,218,0,Residential
-2026-08-07,23.8,,0,0.0,1228.69,612.75,281.98,219,0,Residential
-2026-08-08,0.0,,0,0.0,1325.93,661.24,304.3,220,1,Residential
-2026-08-09,18.4,,0,0.0,1393.9,695.14,319.9,221,1,Residential
-2026-08-10,27.2,,0,0.0,1171.09,584.02,268.77,222,0,Residential
-2026-08-11,0.0,,0,0.0,1157.77,577.38,265.71,223,0,Residential
-2026-08-12,26.1,,0,0.0,1114.41,555.76,255.76,224,0,Residential
-2026-08-13,43.9,,0,0.0,1203.8,600.34,276.27,225,0,Residential
-2026-08-14,25.7,,0,0.0,1192.9,594.9,273.77,226,0,Residential
-2026-08-15,26.2,HUT RI ke-81,1,1.8,1688.51,842.06,387.51,227,1,Tourism
-2026-08-16,0.0,HUT RI ke-81,1,3.3,1853.79,924.49,425.44,228,1,Tourism
-2026-08-17,15.6,HUT RI ke-81,1,4.0,1809.94,902.62,415.38,229,0,Tourism
-2026-08-18,0.0,HUT RI ke-81,1,3.3,1741.77,868.62,399.74,230,0,Tourism
-2026-08-19,30.2,HUT RI ke-81,1,1.8,1548.15,772.06,355.3,231,0,Tourism
-2026-08-20,0.0,,0,0.0,1031.94,514.63,236.83,232,0,Residential
-2026-08-21,25.9,,0,0.0,1113.72,555.41,255.6,233,0,Residential
-2026-08-22,0.0,,0,0.0,1211.49,604.17,278.04,234,1,Residential
-2026-08-23,24.6,,0,0.0,1303.86,650.23,299.24,235,1,Residential
-2026-08-24,0.0,,0,0.0,1128.57,562.82,259.01,236,0,Residential
-2026-08-25,19.5,,0,0.0,1156.89,576.94,265.51,237,0,Residential
-2026-08-26,17.1,,0,0.0,1198.25,597.57,275.0,238,0,Residential
-2026-08-27,0.0,,0,0.0,1195.31,596.1,274.32,239,0,Residential
-2026-08-28,21.4,,0,0.0,1182.37,589.65,271.35,240,0,Residential
-2026-08-29,9.5,,0,0.0,1212.5,604.67,278.27,241,1,Residential
-2026-08-30,9.3,,0,0.0,1261.2,628.96,289.45,242,1,Residential
-2026-08-31,0.0,,0,0.0,1162.08,579.53,266.7,243,0,Residential
-2026-09-01,0.0,,0,0.0,1157.85,577.42,265.73,244,0,Residential
-2026-09-02,9.1,,0,0.0,1080.53,538.86,247.98,245,0,Residential
-2026-09-03,0.0,,0,0.0,1094.29,545.72,251.14,246,0,Residential
-2026-09-04,16.4,,0,0.0,1092.75,544.95,250.79,247,0,Residential
-2026-09-05,10.4,,0,0.0,987.42,492.43,226.61,248,1,Residential
-2026-09-06,11.4,,0,0.0,1095.05,546.1,251.31,249,1,Residential
-2026-09-07,31.2,,0,0.0,1151.06,574.03,264.17,250,0,Residential
-2026-09-08,18.6,,0,0.0,1154.8,575.9,265.03,251,0,Residential
-2026-09-09,17.1,,0,0.0,1090.63,543.9,250.3,252,0,Residential
-2026-09-10,16.4,,0,0.0,1158.39,577.69,265.85,253,0,Residential
-2026-09-11,19.9,,0,0.0,1152.3,574.65,264.45,254,0,Residential
-2026-09-12,0.0,,0,0.0,1241.85,619.31,285.0,255,1,Residential
-2026-09-13,0.0,,0,0.0,1366.75,681.6,313.67,256,1,Residential
-2026-09-14,23.7,Food & Culture Expo,1,1.8,1586.21,791.04,364.04,257,0,Tourism
-2026-09-15,10.9,Food & Culture Expo,1,2.5,1524.71,760.37,349.92,258,0,Tourism
-2026-09-16,19.9,Food & Culture Expo,1,1.8,1602.81,799.32,367.84,259,0,Tourism
-2026-09-17,9.2,,0,0.0,1118.5,557.8,256.7,260,0,Residential
-2026-09-18,0.0,,0,0.0,1134.77,565.91,260.43,261,0,Residential
-2026-09-19,2.9,,0,0.0,1151.23,574.12,264.21,262,1,Residential
-2026-09-20,0.0,,0,0.0,1265.47,631.09,290.43,263,1,Residential
-2026-09-21,14.8,,0,0.0,1231.35,614.07,282.59,264,0,Residential
-2026-09-22,19.1,,0,0.0,1228.88,612.84,282.03,265,0,Residential
-2026-09-23,12.5,,0,0.0,1165.05,581.01,267.38,266,0,Residential
-2026-09-24,11.3,,0,0.0,1130.59,563.83,259.47,267,0,Residential
-2026-09-25,5.2,,0,0.0,1172.03,584.49,268.98,268,0,Residential
-2026-09-26,10.0,,0,0.0,1228.18,612.49,281.87,269,1,Residential
-2026-09-27,0.0,,0,0.0,1228.48,612.64,281.94,270,1,Residential
-2026-09-28,0.0,,0,0.0,1076.39,536.8,247.03,271,0,Residential
-2026-09-29,0.0,,0,0.0,1088.2,542.69,249.74,272,0,Residential
-2026-09-30,13.5,,0,0.0,1072.36,534.79,246.11,273,0,Residential
-2026-10-01,0.0,,0,0.0,1159.44,578.21,266.09,274,0,Residential
-2026-10-02,8.7,,0,0.0,1061.84,529.54,243.69,275,0,Residential
-2026-10-03,0.0,,0,0.0,1083.46,540.32,248.65,276,1,Residential
-2026-10-04,0.0,,0,0.0,1036.04,516.67,237.77,277,1,Residential
-2026-10-05,1.6,,0,0.0,960.74,479.12,220.49,278,0,Residential
-2026-10-06,0.0,,0,0.0,970.83,484.15,222.81,279,0,Residential
-2026-10-07,0.0,,0,0.0,1030.23,513.78,236.44,280,0,Residential
-2026-10-08,7.8,,0,0.0,1051.25,524.26,241.26,281,0,Residential
-2026-10-09,12.6,Jakarta Marathon,1,1.4,1267.7,632.2,290.94,282,0,Tourism
-2026-10-10,0.0,Jakarta Marathon,1,3.0,1591.74,793.8,365.3,283,1,Tourism
-2026-10-11,0.0,Jakarta Marathon,1,1.4,1480.01,738.08,339.66,284,1,Tourism
-2026-10-12,0.0,,0,0.0,1154.37,575.68,264.93,285,0,Residential
-2026-10-13,23.0,,0,0.0,1137.95,567.5,261.16,286,0,Residential
-2026-10-14,0.0,,0,0.0,1207.07,601.97,277.02,287,0,Residential
-2026-10-15,13.0,,0,0.0,1199.22,598.05,275.22,288,0,Residential
-2026-10-16,4.8,,0,0.0,1174.15,585.55,269.47,289,0,Residential
-2026-10-17,0.0,,0,0.0,1210.3,603.58,277.76,290,1,Residential
-2026-10-18,0.0,,0,0.0,1208.7,602.78,277.4,291,1,Residential
-2026-10-19,0.0,,0,0.0,1033.53,515.42,237.2,292,0,Residential
-2026-10-20,0.0,,0,0.0,1004.81,501.1,230.6,293,0,Residential
-2026-10-21,9.6,,0,0.0,1092.89,545.02,250.82,294,0,Residential
-2026-10-22,16.8,,0,0.0,1145.34,571.18,262.86,295,0,Residential
-2026-10-23,0.0,,0,0.0,1064.46,530.85,244.29,296,0,Residential
-2026-10-24,0.0,,0,0.0,1098.36,547.75,252.07,297,1,Residential
-2026-10-25,16.6,,0,0.0,1175.09,586.02,269.68,298,1,Residential
-2026-10-26,0.0,,0,0.0,1075.67,536.44,246.87,299,0,Residential
-2026-10-27,0.0,,0,0.0,1087.48,542.33,249.58,300,0,Residential
-2026-10-28,0.0,,0,0.0,1126.69,561.88,258.58,301,0,Residential
-2026-10-29,0.0,,0,0.0,1073.27,535.24,246.32,302,0,Residential
-2026-10-30,0.0,,0,0.0,1072.46,534.84,246.13,303,0,Residential
-2026-10-31,0.0,,0,0.0,1091.02,544.09,250.39,304,1,Residential
-2026-11-01,0.0,,0,0.0,1139.56,568.3,261.53,305,1,Residential
-2026-11-02,0.0,,0,0.0,1102.99,550.06,253.14,306,0,Residential
-2026-11-03,0.7,,0,0.0,1063.13,530.18,243.99,307,0,Residential
-2026-11-04,0.0,,0,0.0,979.44,488.45,224.78,308,0,Residential
-2026-11-05,0.0,,0,0.0,1042.88,520.08,239.34,309,0,Residential
-2026-11-06,0.0,,0,0.0,1089.48,543.32,250.04,310,0,Residential
-2026-11-07,0.0,,0,0.0,1105.66,551.39,253.75,311,1,Residential
-2026-11-08,7.0,,0,0.0,1181.19,589.06,271.08,312,1,Residential
-2026-11-09,0.0,,0,0.0,1139.02,568.03,261.41,313,0,Residential
-2026-11-10,2.8,,0,0.0,1169.42,583.19,268.38,314,0,Residential
-2026-11-11,0.0,,0,0.0,1144.95,570.99,262.77,315,0,Residential
-2026-11-12,5.1,,0,0.0,1092.95,545.05,250.83,316,0,Residential
-2026-11-13,0.0,,0,0.0,1083.25,540.22,248.61,317,0,Residential
-2026-11-14,0.0,,0,0.0,1130.69,563.88,259.49,318,1,Residential
-2026-11-15,0.0,,0,0.0,1107.53,552.33,254.18,319,1,Residential
-2026-11-16,0.0,,0,0.0,916.92,457.27,210.43,320,0,Residential
-2026-11-17,0.0,,0,0.0,954.94,476.23,219.16,321,0,Residential
-2026-11-18,0.0,,0,0.0,967.1,482.29,221.95,322,0,Residential
-2026-11-19,1.2,,0,0.0,1030.06,513.69,236.4,323,0,Residential
-2026-11-20,0.0,,0,0.0,1055.09,526.17,242.14,324,0,Residential
-2026-11-21,0.0,,0,0.0,1131.35,564.2,259.64,325,1,Residential
-2026-11-22,1.3,,0,0.0,1147.99,572.5,263.46,326,1,Residential
-2026-11-23,0.0,,0,0.0,1050.8,524.03,241.16,327,0,Residential
-2026-11-24,0.0,Ancol Music Fest,1,1.4,1327.34,661.94,304.62,328,0,Tourism
-2026-11-25,9.1,Ancol Music Fest,1,3.0,1532.54,764.28,351.72,329,0,Tourism
-2026-11-26,0.7,Ancol Music Fest,1,1.4,1395.51,695.94,320.27,330,0,Tourism
-2026-11-27,0.0,,0,0.0,1066.82,532.02,244.84,331,0,Residential
-2026-11-28,5.7,,0,0.0,1069.89,533.55,245.54,332,1,Residential
-2026-11-29,0.0,,0,0.0,1141.63,569.33,262.0,333,1,Residential
-2026-11-30,0.0,,0,0.0,1050.37,523.82,241.06,334,0,Residential
-2026-12-01,0.0,,0,0.0,1061.99,529.61,243.73,335,0,Residential
-2026-12-02,0.0,,0,0.0,1047.7,522.49,240.45,336,0,Residential
-2026-12-03,0.0,,0,0.0,1070.87,534.04,245.76,337,0,Residential
-2026-12-04,6.5,,0,0.0,1098.7,547.92,252.15,338,0,Residential
-2026-12-05,0.0,,0,0.0,1159.19,578.09,266.03,339,1,Residential
-2026-12-06,1.0,,0,0.0,1169.48,583.22,268.4,340,1,Residential
-2026-12-07,0.0,,0,0.0,1016.41,506.88,233.27,341,0,Residential
-2026-12-08,11.3,,0,0.0,1004.74,501.06,230.59,342,0,Residential
-2026-12-09,0.0,,0,0.0,1053.13,525.2,241.69,343,0,Residential
-2026-12-10,0.0,,0,0.0,1108.26,552.69,254.35,344,0,Residential
-2026-12-11,0.0,,0,0.0,1025.47,511.4,235.35,345,0,Residential
-2026-12-12,11.7,,0,0.0,1079.56,538.38,247.76,346,1,Residential
-2026-12-13,0.0,,0,0.0,1171.86,584.41,268.94,347,1,Residential
-2026-12-14,0.0,,0,0.0,1109.91,553.51,254.72,348,0,Residential
-2026-12-15,0.0,,0,0.0,1122.56,559.82,257.63,349,0,Residential
-2026-12-16,0.0,,0,0.0,1168.55,582.76,268.18,350,0,Residential
-2026-12-17,0.0,,0,0.0,1203.69,600.28,276.25,351,0,Residential
-2026-12-18,3.4,Christmas Market,1,2.1,1445.72,720.98,331.79,352,0,Tourism
-2026-12-19,0.0,Christmas Market,1,3.1,1559.14,777.54,357.82,353,1,Tourism
-2026-12-20,0.0,Christmas Market,1,3.5,1708.29,851.92,392.05,354,1,Tourism
-2026-12-21,7.5,Christmas Market,1,3.1,1457.21,726.71,334.43,355,0,Tourism
-2026-12-22,5.1,Christmas Market,1,2.1,1410.85,703.59,323.79,356,0,Tourism
-2026-12-23,7.3,,0,0.0,1171.39,584.17,268.83,357,0,Residential
-2026-12-24,0.0,,0,0.0,1133.24,565.15,260.08,358,0,Residential
-2026-12-25,2.9,,0,0.0,1123.76,560.42,257.9,359,0,Residential
-2026-12-26,0.0,,0,0.0,1197.6,597.24,274.85,360,1,Residential
-2026-12-27,0.0,,0,0.0,1198.69,597.79,275.1,361,1,Residential
-2026-12-28,0.0,,0,0.0,1050.24,523.75,241.03,362,0,Residential
-2026-12-29,0.0,,0,0.0,1142.55,569.79,262.22,363,0,Residential
-2026-12-30,0.0,Countdown Jakarta 2027,1,3.2,1641.85,818.79,376.8,364,0,Tourism
-2026-12-31,10.7,Countdown Jakarta 2027,1,4.5,1756.35,875.89,403.08,365,0,Tourism
+2026-01-01,12.8,New Year Countdown,1,4.0,11872.42,5920.78,2724.72,1,0,Tourism
+2026-01-02,18.3,New Year Countdown,1,2.8,11761.19,5865.31,2699.19,2,0,Tourism
+2026-01-03,17.6,,0,0.0,7983.22,3981.23,1832.15,3,1,Residential
+2026-01-04,4.7,,0,0.0,8320.34,4149.35,1909.52,4,1,Residential
+2026-01-05,0.0,,0,0.0,7345.45,3663.18,1685.78,5,0,Residential
+2026-01-06,0.0,,0,0.0,7686.35,3833.18,1764.02,6,0,Residential
+2026-01-07,11.0,,0,0.0,8095.64,4037.3,1857.95,7,0,Residential
+2026-01-08,6.2,,0,0.0,7793.24,3886.49,1788.55,8,0,Residential
+2026-01-09,0.0,,0,0.0,7552.09,3766.23,1733.2,9,0,Residential
+2026-01-10,0.0,,0,0.0,7982.59,3980.92,1832.0,10,1,Residential
+2026-01-11,0.2,,0,0.0,8934.73,4455.75,2050.52,11,1,Residential
+2026-01-12,0.0,,0,0.0,7735.42,3857.65,1775.28,12,0,Residential
+2026-01-13,0.0,,0,0.0,7271.18,3626.14,1668.74,13,0,Residential
+2026-01-14,6.3,,0,0.0,7300.16,3640.59,1675.39,14,0,Residential
+2026-01-15,6.6,,0,0.0,7300.09,3640.55,1675.37,15,0,Residential
+2026-01-16,0.0,,0,0.0,7712.04,3845.99,1769.91,16,0,Residential
+2026-01-17,0.0,,0,0.0,7926.59,3952.99,1819.15,17,1,Residential
+2026-01-18,4.1,Car Free Day,1,1.5,10213.28,5093.36,2343.95,18,1,Tourism
+2026-01-19,0.0,,0,0.0,7923.02,3951.21,1818.33,19,0,Residential
+2026-01-20,0.0,,0,0.0,8218.14,4098.39,1886.06,20,0,Residential
+2026-01-21,0.0,,0,0.0,8169.28,4074.02,1874.85,21,0,Residential
+2026-01-22,0.0,,0,0.0,7729.26,3854.58,1773.87,22,0,Residential
+2026-01-23,0.0,,0,0.0,8343.51,4160.91,1914.84,23,0,Residential
+2026-01-24,0.0,,0,0.0,9262.82,4619.37,2125.82,24,1,Residential
+2026-01-25,19.1,,0,0.0,9938.39,4956.28,2280.86,25,1,Residential
+2026-01-26,0.0,,0,0.0,8687.91,4332.66,1993.88,26,0,Residential
+2026-01-27,2.0,,0,0.0,7872.55,3926.04,1806.75,27,0,Residential
+2026-01-28,0.0,,0,0.0,7847.98,3913.79,1801.11,28,0,Residential
+2026-01-29,2.4,,0,0.0,6908.23,3445.13,1585.44,29,0,Residential
+2026-01-30,0.0,,0,0.0,7002.73,3492.26,1607.13,30,0,Residential
+2026-01-31,0.0,,0,0.0,7321.09,3651.03,1680.19,31,1,Residential
+2026-02-01,6.6,,0,0.0,7937.23,3958.3,1821.59,32,1,Residential
+2026-02-02,0.0,,0,0.0,6917.4,3449.71,1587.54,33,0,Residential
+2026-02-03,7.7,,0,0.0,7264.04,3622.58,1667.1,34,0,Residential
+2026-02-04,0.3,,0,0.0,7423.99,3702.34,1703.81,35,0,Residential
+2026-02-05,0.0,,0,0.0,7857.78,3918.67,1803.36,36,0,Residential
+2026-02-06,1.8,,0,0.0,8308.02,4143.21,1906.69,37,0,Residential
+2026-02-07,0.0,,0,0.0,8772.19,4374.69,2013.22,38,1,Residential
+2026-02-08,0.0,,0,0.0,8918.77,4447.79,2046.86,39,1,Residential
+2026-02-09,12.6,,0,0.0,8198.89,4088.79,1881.65,40,0,Residential
+2026-02-10,7.5,,0,0.0,8452.22,4215.12,1939.78,41,0,Residential
+2026-02-11,0.0,,0,0.0,7798.84,3889.28,1789.83,42,0,Residential
+2026-02-12,0.0,,0,0.0,8164.87,4071.82,1873.84,43,0,Residential
+2026-02-13,0.0,,0,0.0,8486.66,4232.3,1947.69,44,0,Residential
+2026-02-14,7.5,,0,0.0,8775.55,4376.37,2013.99,45,1,Residential
+2026-02-15,1.5,Imlek & Glodok Festival,1,1.1,10392.83,5182.9,2385.15,46,1,Tourism
+2026-02-16,10.6,Imlek & Glodok Festival,1,2.1,10017.91,4995.93,2299.11,47,0,Tourism
+2026-02-17,0.0,Imlek & Glodok Festival,1,2.5,10701.04,5336.61,2455.89,48,0,Tourism
+2026-02-18,2.0,Imlek & Glodok Festival,1,2.1,10150.98,5062.29,2329.65,49,0,Tourism
+2026-02-19,0.0,Imlek & Glodok Festival,1,1.1,9372.79,4674.21,2151.06,50,0,Tourism
+2026-02-20,5.6,,0,0.0,7986.23,3982.73,1832.84,51,0,Residential
+2026-02-21,0.0,,0,0.0,8184.82,4081.77,1878.42,52,1,Residential
+2026-02-22,0.0,,0,0.0,8342.53,4160.42,1914.61,53,1,Residential
+2026-02-23,0.0,,0,0.0,8087.1,4033.04,1855.99,54,0,Residential
+2026-02-24,0.0,,0,0.0,8133.23,4056.04,1866.58,55,0,Residential
+2026-02-25,0.0,,0,0.0,7965.44,3972.36,1828.07,56,0,Residential
+2026-02-26,14.6,,0,0.0,8564.29,4271.01,1965.5,57,0,Residential
+2026-02-27,1.0,,0,0.0,8815.31,4396.2,2023.11,58,0,Residential
+2026-02-28,0.0,,0,0.0,8936.13,4456.45,2050.84,59,1,Residential
+2026-03-01,0.0,,0,0.0,9325.47,4650.61,2140.2,60,1,Residential
+2026-03-02,3.1,,0,0.0,8294.79,4136.61,1903.65,61,0,Residential
+2026-03-03,0.0,,0,0.0,8664.6,4321.04,1988.53,62,0,Residential
+2026-03-04,1.2,,0,0.0,8977.36,4477.01,2060.3,63,0,Residential
+2026-03-05,0.0,,0,0.0,8601.53,4289.58,1974.05,64,0,Residential
+2026-03-06,5.4,,0,0.0,8981.7,4479.17,2061.3,65,0,Residential
+2026-03-07,14.1,,0,0.0,9866.15,4920.25,2264.28,66,1,Residential
+2026-03-08,0.0,,0,0.0,9644.74,4809.83,2213.47,67,1,Residential
+2026-03-09,0.0,,0,0.0,8195.04,4086.87,1880.76,68,0,Residential
+2026-03-10,8.3,,0,0.0,8233.33,4105.96,1889.55,69,0,Residential
+2026-03-11,0.0,,0,0.0,7949.97,3964.65,1824.52,70,0,Residential
+2026-03-12,0.0,,0,0.0,7790.65,3885.2,1787.95,71,0,Residential
+2026-03-13,0.0,,0,0.0,7955.78,3967.55,1825.85,72,0,Residential
+2026-03-14,6.0,,0,0.0,8952.02,4464.37,2054.49,73,1,Residential
+2026-03-15,0.0,,0,0.0,9355.57,4665.62,2147.1,74,1,Residential
+2026-03-16,14.5,,0,0.0,8259.44,4118.98,1895.54,75,0,Residential
+2026-03-17,16.9,,0,0.0,8260.7,4119.61,1895.83,76,0,Residential
+2026-03-18,9.8,H-3 Lebaran,1,2.7,9233.14,4604.57,2119.01,77,0,Residential
+2026-03-19,14.3,H-3 Lebaran,1,4.0,10075.66,5024.73,2312.36,78,0,Residential
+2026-03-20,9.3,Idul Fitri,1,2.3,12573.33,6270.32,2885.58,79,0,Residential
+2026-03-21,0.0,Idul Fitri,1,4.1,13141.17,6553.5,3015.9,80,1,Residential
+2026-03-22,1.5,Idul Fitri,1,5.0,14889.42,7425.35,3417.12,81,1,Residential
+2026-03-23,18.4,Idul Fitri,1,4.1,11068.96,5520.09,2540.33,82,0,Residential
+2026-03-24,0.0,Idul Fitri,1,2.3,9368.73,4672.19,2150.12,83,0,Residential
+2026-03-25,16.8,,0,0.0,8810.83,4393.96,2022.09,84,0,Residential
+2026-03-26,17.6,,0,0.0,8775.2,4376.19,2013.91,85,0,Residential
+2026-03-27,17.9,,0,0.0,9026.78,4501.66,2071.65,86,0,Residential
+2026-03-28,0.0,,0,0.0,9158.1,4567.14,2101.78,87,1,Residential
+2026-03-29,13.7,,0,0.0,9273.32,4624.6,2128.23,88,1,Residential
+2026-03-30,11.7,,0,0.0,8154.72,4066.76,1871.51,89,0,Residential
+2026-03-31,0.0,,0,0.0,7614.74,3797.47,1747.58,90,0,Residential
+2026-04-01,0.0,,0,0.0,8156.89,4067.84,1872.01,91,0,Residential
+2026-04-02,27.3,,0,0.0,8023.47,4001.3,1841.39,92,0,Residential
+2026-04-03,0.0,,0,0.0,8283.66,4131.06,1901.1,93,0,Residential
+2026-04-04,9.7,,0,0.0,9034.13,4505.32,2073.33,94,1,Residential
+2026-04-05,0.0,,0,0.0,8940.05,4458.4,2051.74,95,1,Residential
+2026-04-06,0.0,,0,0.0,8452.78,4215.4,1939.91,96,0,Residential
+2026-04-07,24.4,,0,0.0,8552.11,4264.94,1962.71,97,0,Residential
+2026-04-08,12.3,,0,0.0,8654.17,4315.83,1986.13,98,0,Residential
+2026-04-09,0.0,Jakarta Art Festival,1,1.4,10068.03,5020.93,2310.61,99,0,Tourism
+2026-04-10,14.8,Jakarta Art Festival,1,2.0,11016.25,5493.8,2528.23,100,0,Tourism
+2026-04-11,9.0,Jakarta Art Festival,1,1.4,10566.22,5269.37,2424.95,101,1,Tourism
+2026-04-12,0.0,,0,0.0,8977.57,4477.11,2060.35,102,1,Residential
+2026-04-13,11.8,,0,0.0,8521.17,4249.51,1955.61,103,0,Residential
+2026-04-14,27.3,,0,0.0,8361.64,4169.95,1919.0,104,0,Residential
+2026-04-15,0.0,,0,0.0,8347.64,4162.97,1915.78,105,0,Residential
+2026-04-16,0.0,,0,0.0,8612.1,4294.85,1976.48,106,0,Residential
+2026-04-17,13.1,,0,0.0,8660.12,4318.8,1987.5,107,0,Residential
+2026-04-18,12.4,,0,0.0,9445.24,4710.34,2167.68,108,1,Residential
+2026-04-19,0.0,,0,0.0,10047.38,5010.63,2305.87,109,1,Residential
+2026-04-20,0.0,,0,0.0,9409.75,4692.64,2159.54,110,0,Residential
+2026-04-21,7.2,,0,0.0,9347.59,4661.64,2145.27,111,0,Residential
+2026-04-22,24.3,,0,0.0,9156.98,4566.59,2101.53,112,0,Residential
+2026-04-23,0.0,,0,0.0,9537.92,4756.56,2188.95,113,0,Residential
+2026-04-24,0.0,,0,0.0,9223.62,4599.82,2116.82,114,0,Residential
+2026-04-25,23.4,,0,0.0,9844.38,4909.39,2259.29,115,1,Residential
+2026-04-26,0.0,,0,0.0,9228.52,4602.26,2117.95,116,1,Residential
+2026-04-27,0.0,,0,0.0,8227.66,4103.13,1888.25,117,0,Residential
+2026-04-28,37.7,,0,0.0,8795.5,4386.32,2018.57,118,0,Residential
+2026-04-29,14.3,,0,0.0,8246.28,4112.42,1892.52,119,0,Residential
+2026-04-30,0.0,May Day Rally,1,1.4,10334.87,5154.0,2371.85,120,0,Tourism
+2026-05-01,14.5,May Day Rally,1,3.0,11826.71,5897.98,2714.23,121,0,Tourism
+2026-05-02,13.4,May Day Rally,1,1.4,10983.35,5477.4,2520.68,122,1,Tourism
+2026-05-03,10.0,,0,0.0,8964.41,4470.55,2057.33,123,1,Residential
+2026-05-04,0.0,,0,0.0,8171.45,4075.1,1875.35,124,0,Residential
+2026-05-05,26.7,,0,0.0,8485.47,4231.7,1947.42,125,0,Residential
+2026-05-06,0.0,,0,0.0,8332.31,4155.32,1912.27,126,0,Residential
+2026-05-07,0.0,,0,0.0,8393.07,4185.62,1926.21,127,0,Residential
+2026-05-08,30.7,,0,0.0,9169.65,4572.9,2104.43,128,0,Residential
+2026-05-09,30.6,,0,0.0,9689.96,4832.38,2223.85,129,1,Residential
+2026-05-10,35.5,,0,0.0,9431.73,4703.6,2164.58,130,1,Residential
+2026-05-11,30.4,,0,0.0,8335.67,4157.0,1913.04,131,0,Residential
+2026-05-12,18.5,,0,0.0,9000.88,4488.74,2065.7,132,0,Residential
+2026-05-13,27.4,,0,0.0,8325.87,4152.11,1910.79,133,0,Residential
+2026-05-14,23.7,,0,0.0,8316.07,4147.22,1908.54,134,0,Residential
+2026-05-15,0.0,,0,0.0,8758.96,4368.09,2010.18,135,0,Residential
+2026-05-16,0.0,,0,0.0,8331.68,4155.01,1912.12,136,1,Residential
+2026-05-17,0.0,,0,0.0,9372.44,4674.04,2150.97,137,1,Residential
+2026-05-18,23.7,,0,0.0,9022.44,4499.49,2070.65,138,0,Residential
+2026-05-19,0.0,,0,0.0,8629.88,4303.72,1980.56,139,0,Residential
+2026-05-20,34.7,,0,0.0,8905.4,4441.12,2043.79,140,0,Residential
+2026-05-21,21.7,,0,0.0,8557.5,4267.63,1963.95,141,0,Residential
+2026-05-22,0.0,,0,0.0,8682.45,4329.94,1992.62,142,0,Residential
+2026-05-23,32.7,,0,0.0,9279.69,4627.78,2129.69,143,1,Residential
+2026-05-24,0.0,,0,0.0,8854.02,4415.5,2032.0,144,1,Residential
+2026-05-25,9.7,,0,0.0,8538.53,4258.16,1959.59,145,0,Residential
+2026-05-26,30.3,,0,0.0,8510.18,4244.03,1953.09,146,0,Residential
+2026-05-27,25.1,,0,0.0,8753.5,4365.37,2008.93,147,0,Residential
+2026-05-28,19.0,,0,0.0,8888.67,4432.78,2039.95,148,0,Residential
+2026-05-29,36.3,PRJ Opening,1,2.3,12525.03,6246.23,2874.49,149,0,Tourism
+2026-05-30,11.0,PRJ Opening,1,3.1,13960.66,6962.18,3203.97,150,1,Tourism
+2026-05-31,0.0,PRJ Opening,1,3.8,15014.09,7487.53,3445.73,151,1,Tourism
+2026-06-01,19.9,PRJ Opening,1,4.0,14844.55,7402.98,3406.82,152,0,Tourism
+2026-06-02,0.0,PRJ Opening,1,3.8,12986.61,6476.42,2980.43,153,0,Tourism
+2026-06-03,24.2,PRJ Opening,1,3.1,11239.69,5605.23,2579.51,154,0,Tourism
+2026-06-04,0.0,PRJ Opening,1,2.3,10888.99,5430.34,2499.02,155,0,Tourism
+2026-06-05,15.3,,0,0.0,9440.2,4707.83,2166.53,156,0,Residential
+2026-06-06,0.0,,0,0.0,9880.22,4927.27,2267.51,157,1,Residential
+2026-06-07,15.3,,0,0.0,10435.04,5203.95,2394.84,158,1,Residential
+2026-06-08,25.0,,0,0.0,9570.47,4772.79,2196.42,159,0,Residential
+2026-06-09,0.0,,0,0.0,9518.81,4747.03,2184.57,160,0,Residential
+2026-06-10,17.8,,0,0.0,9271.22,4623.56,2127.74,161,0,Residential
+2026-06-11,32.6,,0,0.0,9224.18,4600.1,2116.95,162,0,Residential
+2026-06-12,25.4,,0,0.0,9293.06,4634.45,2132.76,163,0,Residential
+2026-06-13,39.8,,0,0.0,9287.11,4631.48,2131.39,164,1,Residential
+2026-06-14,0.0,Music Festival GBK,1,1.6,11919.18,5944.1,2735.45,165,1,Tourism
+2026-06-15,29.6,Music Festival GBK,1,3.5,12700.24,6333.61,2914.71,166,0,Tourism
+2026-06-16,33.7,Music Festival GBK,1,1.6,11831.33,5900.28,2715.29,167,0,Tourism
+2026-06-17,0.0,,0,0.0,8253.49,4116.02,1894.18,168,0,Residential
+2026-06-18,35.9,,0,0.0,8990.8,4483.71,2063.39,169,0,Residential
+2026-06-19,22.7,,0,0.0,9638.16,4806.55,2211.96,170,0,Residential
+2026-06-20,33.8,,0,0.0,10419.64,5196.27,2391.31,171,1,Residential
+2026-06-21,34.9,,0,0.0,10489.57,5231.15,2407.36,172,1,Residential
+2026-06-22,0.0,,0,0.0,8771.42,4374.31,2013.04,173,0,Residential
+2026-06-23,27.4,,0,0.0,8978.97,4477.81,2060.67,174,0,Residential
+2026-06-24,0.0,,0,0.0,9485.56,4730.45,2176.94,175,0,Residential
+2026-06-25,0.0,,0,0.0,9968.77,4971.43,2287.83,176,0,Residential
+2026-06-26,36.1,,0,0.0,9780.26,4877.42,2244.57,177,0,Residential
+2026-06-27,0.0,,0,0.0,9225.51,4600.76,2117.25,178,1,Residential
+2026-06-28,26.9,,0,0.0,9894.5,4934.39,2270.79,179,1,Residential
+2026-06-29,34.7,,0,0.0,9638.93,4806.93,2212.13,180,0,Residential
+2026-06-30,0.0,,0,0.0,8962.59,4469.64,2056.91,181,0,Residential
+2026-07-01,26.6,,0,0.0,9029.44,4502.98,2072.26,182,0,Residential
+2026-07-02,0.0,,0,0.0,8703.66,4340.52,1997.49,183,0,Residential
+2026-07-03,8.4,,0,0.0,8944.53,4460.64,2052.77,184,0,Residential
+2026-07-04,0.0,,0,0.0,9452.45,4713.94,2169.34,185,1,Residential
+2026-07-05,12.2,,0,0.0,9809.31,4891.9,2251.24,186,1,Residential
+2026-07-06,0.0,,0,0.0,8221.85,4100.24,1886.91,187,0,Residential
+2026-07-07,0.0,,0,0.0,8923.81,4450.3,2048.01,188,0,Residential
+2026-07-08,31.3,,0,0.0,9313.92,4644.85,2137.54,189,0,Residential
+2026-07-09,0.0,,0,0.0,8364.93,4171.59,1919.75,190,0,Residential
+2026-07-10,38.5,,0,0.0,8396.08,4187.13,1926.9,191,0,Residential
+2026-07-11,22.5,,0,0.0,9079.7,4528.05,2083.79,192,1,Residential
+2026-07-12,28.0,,0,0.0,10164.0,5068.79,2332.64,193,1,Residential
+2026-07-13,31.1,,0,0.0,9447.13,4711.28,2168.12,194,0,Residential
+2026-07-14,23.2,,0,0.0,8683.22,4330.32,1992.8,195,0,Residential
+2026-07-15,45.0,,0,0.0,9224.81,4600.41,2117.09,196,0,Residential
+2026-07-16,27.6,,0,0.0,8161.37,4070.08,1873.03,197,0,Residential
+2026-07-17,30.6,,0,0.0,8251.39,4114.97,1893.69,198,0,Residential
+2026-07-18,40.0,,0,0.0,8947.4,4462.07,2053.43,199,1,Residential
+2026-07-19,35.9,PRJ Peak Weekend,1,3.5,14297.85,7130.34,3281.36,200,1,Tourism
+2026-07-20,0.0,PRJ Peak Weekend,1,5.0,14262.64,7112.78,3273.28,201,0,Tourism
+2026-07-21,21.0,PRJ Peak Weekend,1,3.5,13242.39,6603.98,3039.13,202,0,Tourism
+2026-07-22,0.0,,0,0.0,8856.4,4416.69,2032.54,203,0,Residential
+2026-07-23,32.4,,0,0.0,8475.53,4226.75,1945.13,204,0,Residential
+2026-07-24,22.5,,0,0.0,8638.0,4307.77,1982.42,205,0,Residential
+2026-07-25,0.0,,0,0.0,9289.35,4632.6,2131.91,206,1,Residential
+2026-07-26,28.6,,0,0.0,9849.98,4912.19,2260.57,207,1,Residential
+2026-07-27,25.7,,0,0.0,8674.89,4326.17,1990.89,208,0,Residential
+2026-07-28,0.0,,0,0.0,8254.12,4116.33,1894.32,209,0,Residential
+2026-07-29,18.4,,0,0.0,8717.03,4347.18,2000.56,210,0,Residential
+2026-07-30,19.8,,0,0.0,8743.0,4360.13,2006.52,211,0,Residential
+2026-07-31,30.9,,0,0.0,8807.96,4392.53,2021.43,212,0,Residential
+2026-08-01,0.0,,0,0.0,8549.1,4263.44,1962.02,213,1,Residential
+2026-08-02,0.0,,0,0.0,9007.39,4491.99,2067.2,214,1,Residential
+2026-08-03,17.8,,0,0.0,8525.23,4251.53,1956.54,215,0,Residential
+2026-08-04,0.0,,0,0.0,8857.66,4417.32,2032.83,216,0,Residential
+2026-08-05,0.0,,0,0.0,9041.62,4509.06,2075.05,217,0,Residential
+2026-08-06,19.7,,0,0.0,8650.53,4314.02,1985.3,218,0,Residential
+2026-08-07,23.8,,0,0.0,8600.83,4289.23,1973.89,219,0,Residential
+2026-08-08,0.0,,0,0.0,9281.51,4628.69,2130.11,220,1,Residential
+2026-08-09,18.4,,0,0.0,9757.3,4865.97,2239.3,221,1,Residential
+2026-08-10,27.2,,0,0.0,8197.63,4088.16,1881.36,222,0,Residential
+2026-08-11,0.0,,0,0.0,8104.39,4041.66,1859.96,223,0,Residential
+2026-08-12,26.1,,0,0.0,7800.87,3890.29,1790.3,224,0,Residential
+2026-08-13,43.9,,0,0.0,8426.6,4202.35,1933.9,225,0,Residential
+2026-08-14,25.7,,0,0.0,8350.3,4164.29,1916.39,226,0,Residential
+2026-08-15,26.2,HUT RI ke-81,1,1.8,11819.57,5894.42,2712.59,227,1,Tourism
+2026-08-16,0.0,HUT RI ke-81,1,3.3,12976.53,6471.4,2978.11,228,1,Tourism
+2026-08-17,15.6,HUT RI ke-81,1,4.0,12669.58,6318.32,2907.67,229,0,Tourism
+2026-08-18,0.0,HUT RI ke-81,1,3.3,12192.39,6080.34,2798.15,230,0,Tourism
+2026-08-19,30.2,HUT RI ke-81,1,1.8,10837.05,5404.44,2487.1,231,0,Tourism
+2026-08-20,0.0,,0,0.0,7223.58,3602.4,1657.81,232,0,Residential
+2026-08-21,25.9,,0,0.0,7796.04,3887.89,1789.19,233,0,Residential
+2026-08-22,0.0,,0,0.0,8480.43,4229.19,1946.26,234,1,Residential
+2026-08-23,24.6,,0,0.0,9127.02,4551.64,2094.65,235,1,Residential
+2026-08-24,0.0,,0,0.0,7899.99,3939.73,1813.05,236,0,Residential
+2026-08-25,19.5,,0,0.0,8098.23,4038.59,1858.54,237,0,Residential
+2026-08-26,17.1,,0,0.0,8387.75,4182.97,1924.99,238,0,Residential
+2026-08-27,0.0,,0,0.0,8367.17,4172.71,1920.27,239,0,Residential
+2026-08-28,21.4,,0,0.0,8276.59,4127.54,1899.48,240,0,Residential
+2026-08-29,9.5,,0,0.0,8487.5,4232.72,1947.88,241,1,Residential
+2026-08-30,9.3,,0,0.0,8828.4,4402.72,2026.12,242,1,Residential
+2026-08-31,0.0,,0,0.0,8134.56,4056.71,1866.88,243,0,Residential
+2026-09-01,0.0,,0,0.0,8104.95,4041.94,1860.09,244,0,Residential
+2026-09-02,9.1,,0,0.0,7563.71,3772.02,1735.87,245,0,Residential
+2026-09-03,0.0,,0,0.0,7660.03,3820.06,1757.98,246,0,Residential
+2026-09-04,16.4,,0,0.0,7649.25,3814.68,1755.5,247,0,Residential
+2026-09-05,10.4,,0,0.0,6911.94,3446.98,1586.29,248,1,Residential
+2026-09-06,11.4,,0,0.0,7665.35,3822.71,1759.2,249,1,Residential
+2026-09-07,31.2,,0,0.0,8057.42,4018.24,1849.18,250,0,Residential
+2026-09-08,18.6,,0,0.0,8083.6,4031.29,1855.19,251,0,Residential
+2026-09-09,17.1,,0,0.0,7634.41,3807.28,1752.1,252,0,Residential
+2026-09-10,16.4,,0,0.0,8108.73,4043.82,1860.95,253,0,Residential
+2026-09-11,19.9,,0,0.0,8066.1,4022.56,1851.17,254,0,Residential
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generate_localized_dataset.py

@@ -0,0 +1,138 @@
+import pandas as pd
+import numpy as np
+
+def generate_local_data():
+    print("Starting localized dataset generation...")
+    
+    # Load original dataset
+    try:
+        df_global = pd.read_csv("dataset_vibe_coder_2026.csv")
+    except Exception as e:
+        print(f"Error loading dataset: {e}")
+        return
+
+    # Ensure chronological order
+    df_global['TANGGAL'] = pd.to_datetime(df_global['TANGGAL'])
+    df_global = df_global.sort_values('TANGGAL').reset_index(drop=True)
+
+    # Add lag features on global level (weather is shared across Jakarta)
+    df_global['Rain_Lag_1'] = df_global['RR'].shift(1).fillna(0.0)
+    df_global['Rain_Lag_2'] = df_global['RR'].shift(2).fillna(0.0)
+
+    # Holiday checker for major Indonesian holidays in 2026
+    def get_holiday_flag(date_obj):
+        m, d = date_obj.month, date_obj.day
+        # Specific holiday dates in 2026
+        holidays = {
+            (1, 1),   # New Year
+            (2, 17),  # Imlek
+            (3, 18),  # Nyepi
+            (3, 19),  # Eid al-Fitr Day 1
+            (3, 20),  # Eid al-Fitr Day 2
+            (4, 3),   # Good Friday
+            (5, 1),   # Labor Day
+            (5, 14),  # Ascension Day
+            (5, 27),  # Eid al-Adha Day 1
+            (5, 28),  # Eid al-Adha Day 2
+            (5, 31),  # Waisak
+            (6, 16),  # Islamic New Year
+            (8, 17),  # Independence Day
+            (8, 25),  # Prophet Birthday
+            (12, 25)  # Christmas
+        }
+        # Eid al-Fitr mudik window: March 15 to March 26
+        if m == 3 and (15 <= d <= 26):
+            return 1
+        if (m, d) in holidays:
+            return 1
+        return 0
+
+    df_global['Is_Holiday'] = df_global['TANGGAL'].apply(get_holiday_flag)
+    df_global['Hari_Dalam_Minggu'] = df_global['TANGGAL'].dt.dayofweek
+    df_global['Bulan'] = df_global['TANGGAL'].dt.month
+
+    local_rows = []
+    for idx, row in df_global.iterrows():
+        date_str = row['TANGGAL'].strftime("%Y-%m-%d")
+        global_vol = row['Volume_Total_Ton']
+        rr = row['RR']
+        rain_lag1 = row['Rain_Lag_1']
+        rain_lag2 = row['Rain_Lag_2']
+        is_holiday = row['Is_Holiday']
+        ada_event = row['Ada_Event']
+        crowd_scale = row['Crowd_Scale']
+        hari_ke = row['Hari_Ke']
+        is_weekend = row['Is_Weekend']
+        hari_dalam_minggu = row['Hari_Dalam_Minggu']
+        bulan = row['Bulan']
+        
+        # Apply Lebaran mudik population drop factor
+        # If inside March Lebaran window, drop global base volume by 35%
+        vol_scale = global_vol
+        if is_holiday == 1 and row['TANGGAL'].month == 3:
+            vol_scale = global_vol * 0.65
+            
+        # JIS (North Jakarta)
+        # Base volume: ~120 tons average
+        jis_vol = vol_scale * (120.0 / 7700.0)
+        # Event spikes at Stadium
+        if ada_event == 1:
+            jis_vol += crowd_scale * 15.0
+        # Weekend recreation factor
+        if is_weekend == 1:
+            jis_vol *= 1.05
+        local_rows.append({
+            'Tanggal': date_str, 'Location': 'JIS', 'Volume_Ton': jis_vol,
+            'RR': rr, 'Rain_Lag_1': rain_lag1, 'Rain_Lag_2': rain_lag2,
+            'Is_Holiday': is_holiday, 'Ada_Event': ada_event, 'Crowd_Scale': crowd_scale,
+            'Hari_Ke': hari_ke, 'Is_Weekend': is_weekend, 'Hari_Dalam_Minggu': hari_dalam_minggu, 'Bulan': bulan
+        })
+        
+        # GBK (Central/South)
+        # Base volume: ~85 tons average
+        gbk_vol = vol_scale * (85.0 / 7700.0)
+        # Event spikes at Stadium
+        if ada_event == 1:
+            gbk_vol += crowd_scale * 12.0
+        # Weekend public sports factor
+        if is_weekend == 1:
+            gbk_vol *= 1.15
+        local_rows.append({
+            'Tanggal': date_str, 'Location': 'GBK', 'Volume_Ton': gbk_vol,
+            'RR': rr, 'Rain_Lag_1': rain_lag1, 'Rain_Lag_2': rain_lag2,
+            'Is_Holiday': is_holiday, 'Ada_Event': ada_event, 'Crowd_Scale': crowd_scale,
+            'Hari_Ke': hari_ke, 'Is_Weekend': is_weekend, 'Hari_Dalam_Minggu': hari_dalam_minggu, 'Bulan': bulan
+        })
+        
+        # Pasar Senen (Central)
+        # Base volume: ~45 tons average
+        senen_vol = vol_scale * (45.0 / 7700.0)
+        # Weekday market commerce factor
+        if is_weekend == 0:
+            senen_vol *= 1.10
+        local_rows.append({
+            'Tanggal': date_str, 'Location': 'Pasar Senen', 'Volume_Ton': senen_vol,
+            'RR': rr, 'Rain_Lag_1': rain_lag1, 'Rain_Lag_2': rain_lag2,
+            'Is_Holiday': is_holiday, 'Ada_Event': 0, 'Crowd_Scale': 0,
+            'Hari_Ke': hari_ke, 'Is_Weekend': is_weekend, 'Hari_Dalam_Minggu': hari_dalam_minggu, 'Bulan': bulan
+        })
+        
+        # Gang Sempit Tambora (West)
+        # Base volume: ~8.5 tons average
+        tambora_vol = vol_scale * (8.5 / 7700.0)
+        # Hujan block factor (heavy rain delays alley collection)
+        if rr > 20:
+            tambora_vol *= 0.75
+        local_rows.append({
+            'Tanggal': date_str, 'Location': 'Gang Sempit Tambora', 'Volume_Ton': tambora_vol,
+            'RR': rr, 'Rain_Lag_1': rain_lag1, 'Rain_Lag_2': rain_lag2,
+            'Is_Holiday': is_holiday, 'Ada_Event': 0, 'Crowd_Scale': 0,
+            'Hari_Ke': hari_ke, 'Is_Weekend': is_weekend, 'Hari_Dalam_Minggu': hari_dalam_minggu, 'Bulan': bulan
+        })
+
+    df_local = pd.DataFrame(local_rows)
+    df_local.to_csv("dataset_local_2026.csv", index=False)
+    print("dataset_local_2026.csv generated successfully with 1460 rows!")
+
+if __name__ == "__main__":
+    generate_local_data()

model_sampah_advanced.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:24b98c67674caedfdc434451cf4deb70d69c4e9620e57e80b24cbaddfa3a0287
+size 1287658

scale_dataset.py

@@ -0,0 +1,27 @@
+import pandas as pd
+import numpy as np
+
+# Load dataset
+df = pd.read_csv("dataset_vibe_coder_2026.csv")
+
+print("Original Stats:")
+print(df[["Volume_Total_Ton", "Vol_Sisa_Makanan_Ton", "Vol_Plastik_Ton"]].describe())
+
+# Scale values to match DKI Jakarta daily average (~7,700 tons/day)
+# original mean is ~1,100 tons/day, so we scale by ~7
+scale_factor = 7.0
+
+df["Volume_Total_Ton"] = (df["Volume_Total_Ton"] * scale_factor).round(2)
+
+# Organic/Food waste (Sisa Makanan) is ~49.87% of total
+df["Vol_Sisa_Makanan_Ton"] = (df["Volume_Total_Ton"] * 0.4987).round(2)
+
+# Plastic waste is ~22.95% of total
+df["Vol_Plastik_Ton"] = (df["Volume_Total_Ton"] * 0.2295).round(2)
+
+# Save the scaled dataset
+df.to_csv("dataset_vibe_coder_2026.csv", index=False)
+
+print("\nScaled Stats:")
+print(df[["Volume_Total_Ton", "Vol_Sisa_Makanan_Ton", "Vol_Plastik_Ton"]].describe())
+print("\nDataset successfully scaled to DKI Jakarta Province scale!")

static/app.js

@@ -0,0 +1,609 @@
+// Coordinates and Map Data
+const LOCATION_COORDINATES = {
+    "GBK": {latitude: -6.2183, longitude: 106.8022},
+    "JIS": {latitude: -6.1244, longitude: 106.8622},
+    "Pasar Senen": {latitude: -6.1744, longitude: 106.8444},
+    "Gang Sempit Tambora": {latitude: -6.1500, longitude: 106.8000}
+};
+
+const LOCATION_MAP_DATA = {
+    "JIS": {coords: [-6.1244, 106.8622], label: "JIS"},
+    "GBK": {coords: [-6.2183, 106.8022], label: "GBK"},
+    "Pasar Senen": {coords: [-6.1744, 106.8444], label: "Senen"},
+    "Gang Sempit Tambora": {coords: [-6.1500, 106.8000], label: "Tambora"}
+};
+
+const LOCATION_RADIUS = {
+    "JIS": "1.5 km",
+    "GBK": "2.0 km",
+    "Pasar Senen": "1.2 km",
+    "Gang Sempit Tambora": "0.8 km"
+};
+
+const BANTARGEBANG_COORDS = [-6.3477, 106.9939];
+
+// UI Elements
+const locationSelect = document.getElementById("location-select");
+const modelSelect = document.getElementById("model-select");
+const forecastSlider = document.getElementById("forecast-slider");
+const forecastVal = document.getElementById("forecast-val");
+const rainOverride = document.getElementById("rain-override");
+const rainOverrideVal = document.getElementById("rain-override-val");
+const eventOverride = document.getElementById("event-override");
+const predictBtn = document.getElementById("predict-btn");
+const exportBtn = document.getElementById("export-btn");
+
+// Weather elements
+const weatherForecastText = document.getElementById("weather-forecast-text");
+const weatherLocationText = document.getElementById("weather-location-text");
+const weatherPrecip = document.getElementById("weather-precip");
+const weatherAlert = document.getElementById("weather-alert");
+const eventDescText = document.getElementById("event-desc-text");
+
+// Stats elements
+const statTotalVolume = document.getElementById("stat-total-volume");
+const statRiskStatus = document.getElementById("stat-risk-status");
+const statTrucks = document.getElementById("stat-trucks");
+
+// Metadata elements
+const statPeriodMeta = document.getElementById("stat-period-meta");
+const statLocationMeta = document.getElementById("stat-location-meta");
+
+// Composition elements
+const valOrganic = document.getElementById("val-organic");
+const valPlastic = document.getElementById("val-plastic");
+const barOrganic = document.getElementById("bar-organic");
+const barPlastic = document.getElementById("bar-plastic");
+
+// Logistics elements
+const logManpower = document.getElementById("log-manpower");
+const logDuration = document.getElementById("log-duration");
+const logEfficiency = document.getElementById("log-efficiency");
+const logConfidence = document.getElementById("log-confidence");
+
+// Timeline & Hourly
+const timelineList = document.getElementById("timeline-list");
+const hourlySection = document.getElementById("hourly-section");
+const hourlyGrid = document.getElementById("hourly-grid");
+
+// State
+let selectedLocation = "JIS";
+let rainValue = 0; // 0 means Auto (Open-Meteo)
+let map;
+let mapMarkers = {};
+let routeLine = null;
+
+// Event Listeners for controls
+forecastSlider.addEventListener("input", (e) => {
+    forecastVal.textContent = e.target.value;
+});
+
+rainOverride.addEventListener("input", (e) => {
+    const val = parseInt(e.target.value);
+    rainValue = val;
+    if (val === 0) {
+        rainOverrideVal.textContent = "Auto (Open-Meteo)";
+    } else {
+        rainOverrideVal.textContent = `${val} mm`;
+    }
+    updateRainAnimationIntensity(val);
+});
+
+locationSelect.addEventListener("change", (e) => {
+    selectedLocation = e.target.value;
+    updateActiveMapMarker(selectedLocation);
+    panToLocation(selectedLocation);
+    fetchLiveWeather(selectedLocation);
+});
+
+// Initialize Leaflet Map
+function initMap() {
+    // Centered around Central Jakarta
+    map = L.map('map', {
+        zoomControl: true,
+        attributionControl: false,
+        maxZoom: 15,
+        minZoom: 9
+    }).setView([-6.175, 106.825], 11.5);
+
+    // CartoDB Dark Matter tile layer for premium dark look
+    L.tileLayer('https://{s}.basemaps.cartocdn.com/dark_all/{z}/{x}/{y}{r}.png', {
+        maxZoom: 20
+    }).addTo(map);
+
+    // Add Special Final Disposal Site (TPST Bantargebang) Marker
+    const bantarIcon = L.divIcon({
+        className: 'leaflet-custom-marker bantar-marker',
+        html: `<div class="marker-pulse" style="background:#FF9900;opacity:0.25;"></div><div class="marker-core" style="background:#FF9900;border:2px solid #FFF;"></div><div class="marker-label" style="color:#FF9900;border-color:#FF9900;">Bantargebang</div>`,
+        iconSize: [24, 24],
+        iconAnchor: [12, 12]
+    });
+    L.marker(BANTARGEBANG_COORDS, { icon: bantarIcon }).addTo(map).bindPopup(`
+        <div class="route-popup" style="border-left: 3px solid #FF9900;">
+            <h3 style="color:#FF9900;">TPST BANTARGEBANG</h3>
+            <div>Disposal Facility (Bekasi)</div>
+            <div>Active Capacity: <b>Calibrated</b></div>
+        </div>
+    `);
+
+    // Add Custom Location Markers
+    Object.keys(LOCATION_MAP_DATA).forEach(loc => {
+        const data = LOCATION_MAP_DATA[loc];
+        const customIcon = L.divIcon({
+            className: 'leaflet-custom-marker',
+            html: `<div class="marker-pulse"></div><div class="marker-core"></div><div class="marker-label">${data.label}</div>`,
+            iconSize: [24, 24],
+            iconAnchor: [12, 12]
+        });
+
+        const marker = L.marker(data.coords, { icon: customIcon }).addTo(map);
+
+        // Marker Click logic
+        marker.on('click', () => {
+            selectedLocation = loc;
+            locationSelect.value = loc;
+            updateActiveMapMarker(loc);
+            panToLocation(loc);
+            fetchLiveWeather(loc);
+            runPrediction();
+        });
+
+        // Save reference
+        mapMarkers[loc] = marker;
+    });
+
+    // Initial Active Node highlight
+    setTimeout(() => {
+        updateActiveMapMarker(selectedLocation);
+    }, 1000);
+}
+
+function updateActiveMapMarker(locName) {
+    Object.keys(mapMarkers).forEach(loc => {
+        const marker = mapMarkers[loc];
+        const el = marker.getElement();
+        if (el) {
+            if (loc === locName) {
+                el.classList.add("active");
+            } else {
+                el.classList.remove("active");
+            }
+        }
+    });
+}
+
+function panToLocation(locName) {
+    const coords = LOCATION_MAP_DATA[locName]?.coords;
+    if (coords && map) {
+        map.panTo(coords);
+    }
+}
+
+function updateMarkerRisk(locName, riskStatus) {
+    const marker = mapMarkers[locName];
+    if (marker) {
+        const el = marker.getElement();
+        if (el) {
+            el.classList.remove("safe", "warning", "critical");
+            el.classList.add(riskStatus.toLowerCase());
+        }
+    }
+}
+
+// Draw polyline route to TPST Bantargebang
+function drawTransitRoute(locName) {
+    const startCoords = LOCATION_MAP_DATA[locName]?.coords;
+    if (!startCoords || !map) return;
+
+    if (routeLine) {
+        map.removeLayer(routeLine);
+    }
+
+    // Cyan glowing dashed line representing logistical transit path
+    routeLine = L.polyline([startCoords, BANTARGEBANG_COORDS], {
+        color: '#00F0FF',
+        weight: 3.5,
+        opacity: 0.75,
+        dashArray: '8, 8',
+        className: 'glowing-route'
+    }).addTo(map);
+
+    // Hardcoded logistics profile distance mappings
+    const distanceMap = {
+        "JIS": "41.2 km",
+        "GBK": "38.5 km",
+        "Pasar Senen": "34.8 km",
+        "Gang Sempit Tambora": "43.5 km"
+    };
+
+    const timeMap = {
+        "JIS": "1.5 Hours",
+        "GBK": "1.8 Hours",
+        "Pasar Senen": "1.4 Hours",
+        "Gang Sempit Tambora": "2.1 Hours"
+    };
+
+    routeLine.bindPopup(`
+        <div class="route-popup">
+            <h3>LOGISTICS DISPATCH ROUTE</h3>
+            <div>Start: <b>${locName}</b></div>
+            <div>Destination: <b>TPST Bantargebang</b></div>
+            <div>Transit Distance: <b class="highlight">${distanceMap[locName]}</b></div>
+            <div>Est. Travel Time: <b class="highlight">${timeMap[locName]}</b></div>
+        </div>
+    `).openPopup();
+
+    // Automatically zoom/fit bounds to show both the collection point and Bantargebang nicely
+    map.fitBounds([startCoords, BANTARGEBANG_COORDS], {
+        padding: [60, 60]
+    });
+}
+
+// Fetch Live Weather from Open-Meteo
+async function fetchLiveWeather(loc) {
+    const coord = LOCATION_COORDINATES[loc];
+    if (!coord) return;
+
+    weatherForecastText.textContent = "Fetching...";
+    weatherPrecip.textContent = "0.0 mm";
+    weatherAlert.textContent = "Checking...";
+
+    const url = `https://api.open-meteo.com/v1/forecast?latitude=${coord.latitude}&longitude=${coord.longitude}&current_weather=true&daily=precipitation_sum&timezone=Asia/Jakarta&past_days=2`;
+    
+    try {
+        const response = await fetch(url);
+        if (response.ok) {
+            const data = await response.json();
+            const temp = data.current_weather.temperature;
+            const wind = data.current_weather.windspeed;
+            const code = data.current_weather.weathercode;
+            
+            // Set precip sum for today
+            const dailyData = data.daily || {};
+            const precipList = dailyData.precipitation_sum || [];
+            // past_days=2 means indices: 0 (H-2), 1 (H-1), 2 (H0)
+            const precipToday = precipList[2] || 0;
+            
+            let cond = "Cloudy";
+            if (code === 0) cond = "Clear Sky";
+            else if (code > 0 && code < 4) cond = "Partly Cloudy";
+            else if (code >= 51 && code <= 67) cond = "Rainy";
+            else if (code >= 80 && code <= 82) cond = "Showers";
+
+            weatherForecastText.textContent = `${temp}°C - ${cond}`;
+            weatherLocationText.textContent = `${loc} coordinates`;
+            weatherPrecip.textContent = `${precipToday.toFixed(1)} mm`;
+            
+            if (precipToday > 30) {
+                weatherAlert.textContent = "HEAVY RAIN 🟡";
+                weatherAlert.className = "highlight text-warning";
+            } else if (precipToday > 50) {
+                weatherAlert.textContent = "FLOOD DANGER 🔴";
+                weatherAlert.className = "highlight text-red";
+            } else {
+                weatherAlert.textContent = "Normal conditions";
+                weatherAlert.className = "highlight";
+            }
+        } else {
+            throw new Error("HTTP Error");
+        }
+    } catch (err) {
+        weatherForecastText.textContent = "Weather Unavailable";
+        weatherPrecip.textContent = "N/A";
+        weatherAlert.textContent = "Error fetching";
+    }
+}
+
+// Run prediction calling FastAPI backend
+async function runPrediction() {
+    predictBtn.disabled = true;
+    predictBtn.querySelector(".btn-text").textContent = "PROCESSING FORECAST...";
+
+    const payload = {
+        forecast_days: parseInt(forecastSlider.value),
+        rainfall_mm: parseFloat(rainValue),
+        event_scale: parseInt(eventOverride.value),
+        location: selectedLocation,
+        model_type: modelSelect.value,
+        granularity: forecastSlider.value <= 7 ? "hourly" : "daily" // auto hourly for short horizons
+    };
+
+    try {
+        const response = await fetch("/api/v1/predict", {
+            method: "POST",
+            headers: {
+                "Content-Type": "application/json"
+            },
+            body: JSON.stringify(payload)
+        });
+
+        if (response.ok) {
+            const resData = await response.json();
+            updateDashboardData(resData.data, resData.confidence_score, resData.message);
+        } else {
+            alert("Prediction failed. Make sure the API server is running.");
+        }
+    } catch (err) {
+        console.error(err);
+        alert("Network error connecting to Waste Intelligence API.");
+    } finally {
+        predictBtn.disabled = false;
+        predictBtn.querySelector(".btn-text").textContent = "RUN PREDICTION";
+    }
+}
+
+function updateDashboardData(data, confScore, message) {
+    const results = data.prediction_results;
+    if (results.length === 0) return;
+
+    // Calculate sum of tonnage
+    const totalVolume = results.reduce((acc, curr) => acc + curr.total_volume_ton, 0);
+    const avgVolume = totalVolume / results.length;
+    
+    // Update main cards
+    statTotalVolume.innerHTML = `${totalVolume.toFixed(2)} <span class="unit">Tons</span>`;
+    
+    // Determine overall risk
+    let maxRisk = "SAFE";
+    results.forEach(r => {
+        if (r.risk_status === "CRITICAL") maxRisk = "CRITICAL";
+        else if (r.risk_status === "WARNING" && maxRisk !== "CRITICAL") maxRisk = "WARNING";
+    });
+    
+    statRiskStatus.textContent = maxRisk;
+    statRiskStatus.className = `card-value status-badge ${maxRisk.toLowerCase()}`;
+
+    // Update map marker risk status dynamically
+    updateMarkerRisk(selectedLocation, maxRisk);
+
+    // Draw active logistics route to TPST Bantargebang
+    drawTransitRoute(selectedLocation);
+
+    statTrucks.innerHTML = `${data.logistics_plan.trucks_needed} <span class="unit">Trucks (5T)</span>`;
+
+    // Update metadata labels (Prediction Period & Target Location with Radius)
+    const startDateStr = results[0].date;
+    const endDateStr = results[results.length - 1].date;
+    
+    statPeriodMeta.textContent = `Period: ${startDateStr} to ${endDateStr}`;
+    statLocationMeta.textContent = `${selectedLocation} (Radius ${LOCATION_RADIUS[selectedLocation]})`;
+
+    // Composition Breakdown
+    const totalOrganic = results.reduce((acc, curr) => acc + curr.organic_waste_ton, 0);
+    const totalPlastic = results.reduce((acc, curr) => acc + curr.plastic_waste_ton, 0);
+    
+    valOrganic.textContent = `${totalOrganic.toFixed(2)} Ton`;
+    valPlastic.textContent = `${totalPlastic.toFixed(2)} Ton`;
+
+    const organicPercentage = totalVolume > 0 ? (totalOrganic / totalVolume) * 100 : 0;
+    const plasticPercentage = totalVolume > 0 ? (totalPlastic / totalVolume) * 100 : 0;
+
+    barOrganic.style.width = `${organicPercentage}%`;
+    barPlastic.style.width = `${plasticPercentage}%`;
+
+    // Logistics plan
+    logManpower.textContent = `${data.logistics_plan.manpower} Crew`;
+    logDuration.textContent = `${data.logistics_plan.estimated_duration_hours.toFixed(1)} Hours`;
+    logEfficiency.textContent = data.logistics_plan.efficiency_rate;
+    logConfidence.textContent = `${(confScore * 100).toFixed(1)}%`;
+
+    // Event Info banner
+    const eventDay = results.find(r => r.event_info !== null);
+    if (eventDay) {
+        eventDescText.innerHTML = `⚠️ <strong>${eventDay.event_info}</strong> on ${eventDay.date}. Heavy crowd expected near site.`;
+        document.getElementById("event-box").style.borderColor = "var(--red)";
+    } else {
+        eventDescText.textContent = "No major public events scheduled for this location in the forecast window.";
+        document.getElementById("event-box").style.borderColor = "var(--yellow)";
+    }
+
+    // Daily timeline breakdown cards
+    timelineList.innerHTML = "";
+    results.forEach(day => {
+        const card = document.createElement("div");
+        card.className = "timeline-card";
+        
+        const dateObj = new Date(day.date);
+        const dayName = dateObj.toLocaleDateString('en-US', { weekday: 'short' });
+        const displayDate = `${dayName}, ${dateObj.getDate()} ${dateObj.toLocaleString('en-US', { month: 'short' })}`;
+
+        card.innerHTML = `
+            <span class="timeline-date">${displayDate}</span>
+            <span class="timeline-vol">${day.total_volume_ton.toFixed(1)} T</span>
+            <span class="timeline-status ${day.risk_status.toLowerCase()}">${day.risk_status}</span>
+        `;
+        timelineList.appendChild(card);
+    });
+
+    // Hourly Risk Heatmap
+    const hourlyDay = results[0]; // show hourly for first day if requested
+    if (hourlyDay && hourlyDay.hourly_breakdown) {
+        hourlySection.style.display = "block";
+        hourlyGrid.innerHTML = "";
+        hourlyDay.hourly_breakdown.forEach(hour => {
+            const cell = document.createElement("div");
+            cell.className = "hourly-cell";
+            
+            let intensityClass = "low";
+            if (hour.risk_indicator === "MEDIUM") intensityClass = "medium";
+            else if (hour.risk_indicator === "HIGH") intensityClass = "high";
+
+            cell.innerHTML = `
+                <div class="cell-block ${intensityClass}" title="Vol: ${hour.estimated_volume_ton} Ton - Risk: ${hour.risk_indicator}"></div>
+                <span class="cell-time">${hour.hour}</span>
+            `;
+            hourlyGrid.appendChild(cell);
+        });
+    } else {
+        hourlySection.style.display = "none";
+    }
+}
+
+// Request CSV from Backend API and download it
+async function runExport() {
+    exportBtn.disabled = true;
+    exportBtn.querySelector(".btn-text").textContent = "EXPORTING...";
+
+    const payload = {
+        forecast_days: parseInt(forecastSlider.value),
+        rainfall_mm: parseFloat(rainValue),
+        event_scale: parseInt(eventOverride.value),
+        location: selectedLocation,
+        model_type: modelSelect.value,
+        granularity: forecastSlider.value <= 7 ? "hourly" : "daily"
+    };
+
+    try {
+        const response = await fetch("/api/v1/predict/csv", {
+            method: "POST",
+            headers: {
+                "Content-Type": "application/json"
+            },
+            body: JSON.stringify(payload)
+        });
+
+        if (response.ok) {
+            const blob = await response.blob();
+            const url = window.URL.createObjectURL(blob);
+            const a = document.createElement("a");
+            a.href = url;
+            a.download = `waste_forecast_${selectedLocation.replace(/\s+/g, "_")}_${forecastSlider.value}d.csv`;
+            document.body.appendChild(a);
+            a.click();
+            a.remove();
+            window.URL.revokeObjectURL(url);
+        } else {
+            alert("CSV export failed. Ensure the server is online.");
+        }
+    } catch (err) {
+        console.error(err);
+        alert("Network error connecting to Export API.");
+    } finally {
+        exportBtn.disabled = false;
+        exportBtn.querySelector(".btn-text").textContent = "EXPORT CSV";
+    }
+}
+
+predictBtn.addEventListener("click", runPrediction);
+exportBtn.addEventListener("click", runExport);
+
+// Initial loading setup
+window.addEventListener("DOMContentLoaded", () => {
+    initMap();
+    fetchLiveWeather("JIS");
+    // Run initial prediction after models load
+    setTimeout(runPrediction, 1000);
+});
+
+
+// ==========================================
+// BACKGROUND CANVAS: INTERACTIVE RAIN EFFECT
+// ==========================================
+const canvas = document.getElementById("rain-canvas");
+const ctx = canvas.getContext("2d");
+
+let width = canvas.width = window.innerWidth;
+let height = canvas.height = window.innerHeight;
+
+window.addEventListener("resize", () => {
+    width = canvas.width = window.innerWidth;
+    height = canvas.height = window.innerHeight;
+});
+
+let drops = [];
+let particles = [];
+let maxPrecip = 0; // Current precipitation override
+
+function updateRainAnimationIntensity(precipVal) {
+    maxPrecip = precipVal;
+}
+
+// Particle class for normal state (no rain)
+class DataParticle {
+    constructor() {
+        this.reset();
+    }
+    reset() {
+        this.x = Math.random() * width;
+        this.y = Math.random() * height;
+        this.size = Math.random() * 2 + 1;
+        this.speedX = Math.random() * 0.4 - 0.2;
+        this.speedY = Math.random() * -0.5 - 0.2;
+        this.alpha = Math.random() * 0.5 + 0.1;
+    }
+    update() {
+        this.x += this.speedX;
+        this.y += this.speedY;
+        if (this.y < 0 || this.x < 0 || this.x > width) {
+            this.reset();
+            this.y = height;
+        }
+    }
+    draw() {
+        ctx.fillStyle = `rgba(0, 240, 255, ${this.alpha})`;
+        ctx.beginPath();
+        ctx.arc(this.x, this.y, this.size, 0, Math.PI * 2);
+        ctx.fill();
+    }
+}
+
+// Rain Drop class for rainy state
+class RainDrop {
+    constructor() {
+        this.reset();
+    }
+    reset() {
+        this.x = Math.random() * width;
+        this.y = Math.random() * -100 - 10;
+        this.length = Math.random() * 15 + 10;
+        this.speed = Math.random() * 12 + 15;
+        this.weight = Math.random() * 1 + 0.5;
+        this.alpha = Math.random() * 0.3 + 0.1;
+    }
+    update() {
+        this.y += this.speed;
+        if (this.y > height) {
+            this.reset();
+        }
+    }
+    draw() {
+        ctx.strokeStyle = `rgba(0, 240, 255, ${this.alpha})`;
+        ctx.lineWidth = this.weight;
+        ctx.beginPath();
+        ctx.moveTo(this.x, this.y);
+        ctx.lineTo(this.x + (maxPrecip * 0.05), this.y + this.length);
+        ctx.stroke();
+    }
+}
+
+// Initialize particles and rain drops
+for (let i = 0; i < 60; i++) {
+    particles.push(new DataParticle());
+}
+for (let i = 0; i < 150; i++) {
+    drops.push(new RainDrop());
+}
+
+function animate() {
+    ctx.clearRect(0, 0, width, height);
+    
+    if (maxPrecip === 0) {
+        // Normal floating data particles
+        particles.forEach(p => {
+            p.update();
+            p.draw();
+        });
+    } else {
+        // Cyber rain drops falling
+        // Number of raindrops drawn depends on the rain scale override
+        const activeCount = Math.min(Math.floor(maxPrecip * 1.5), 150);
+        for (let i = 0; i < activeCount; i++) {
+            drops[i].update();
+            drops[i].draw();
+        }
+    }
+    
+    requestAnimationFrame(animate);
+}
+
+animate();

static/index.html

@@ -0,0 +1,217 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Waste Intelligence Dashboard - DKI Jakarta 2026</title>
+    <!-- Google Fonts -->
+    <link rel="preconnect" href="https://fonts.googleapis.com">
+    <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
+    <link href="https://fonts.googleapis.com/css2?family=Outfit:wght@300;400;600;800&family=Space+Grotesk:wght@300;400;500;600;700&family=JetBrains+Mono:wght@300;400;700&display=swap" rel="stylesheet">
+    
+    <!-- Leaflet.js Map Library -->
+    <link rel="stylesheet" href="https://unpkg.com/leaflet@1.9.4/dist/leaflet.css" integrity="sha256-p4NxAoJBhIIN+hmNHrzRCf9tD/miZyoHS5obTRR9BMY=" crossorigin="" />
+    <script src="https://unpkg.com/leaflet@1.9.4/dist/leaflet.js" integrity="sha256-20nQCchB9co0qIjJZRGuk2/Z9VM+kNiyxNV1lvTlZBo=" crossorigin=""></script>
+
+    <link rel="stylesheet" href="/static/style.css">
+</head>
+<body>
+    <!-- Background Canvas for Interactive Particle Rain -->
+    <canvas id="rain-canvas"></canvas>
+
+    <header>
+        <div class="logo-container">
+            <span class="logo-text">WASTE<span class="highlight">INTELLIGENCE</span></span>
+            <span class="version-tag">v3.0.0 (Calibrated)</span>
+        </div>
+        <div class="system-status">
+            <span class="status-indicator online"></span>
+            <span class="status-label">System Online</span>
+        </div>
+    </header>
+
+    <main class="dashboard-grid">
+        <!-- Panel Kontrol (Sidebar) -->
+        <section class="panel control-panel">
+            <h2 class="panel-title">PREDICTION CONFIG</h2>
+            <div class="control-group">
+                <label for="location-select">Target Location</label>
+                <select id="location-select" class="form-control">
+                    <option value="JIS" selected>JIS (North Jakarta)</option>
+                    <option value="GBK">GBK (Central/South Jakarta)</option>
+                    <option value="Pasar Senen">Pasar Senen (Central Jakarta)</option>
+                    <option value="Gang Sempit Tambora">Gang Sempit Tambora (West Jakarta)</option>
+                </select>
+            </div>
+
+            <div class="control-group">
+                <label for="model-select">AI Forecasting Model</label>
+                <select id="model-select" class="form-control">
+                    <option value="chronos">Amazon Chronos-T5 (Tiny)</option>
+                    <option value="gradient_boosting" selected>Gradient Boosting (Real Data - 94.0% Accuracy)</option>
+                </select>
+            </div>
+
+            <div class="control-group">
+                <label for="forecast-slider">Forecast Horizon: <span id="forecast-val" class="value-display">7</span> Days</label>
+                <input type="range" id="forecast-slider" min="1" max="30" value="7" class="slider">
+            </div>
+
+            <div class="divider"></div>
+            <h3 class="panel-subtitle">Simulation Overrides</h3>
+
+            <div class="control-group">
+                <label for="rain-override">Manual Rain Override (mm)</label>
+                <div class="range-override-container">
+                    <input type="range" id="rain-override" min="0" max="100" value="0" class="slider">
+                    <span id="rain-override-val" class="override-display">Auto (Open-Meteo)</span>
+                </div>
+            </div>
+
+            <div class="control-group">
+                <label for="event-override">Crowd Event Scale (0 - 5)</label>
+                <input type="range" id="event-override" min="0" max="5" value="0" class="slider">
+            </div>
+
+            <div class="button-row">
+                <button id="predict-btn" class="action-btn">
+                    <span class="btn-text">RUN PREDICTION</span>
+                    <span class="btn-glow"></span>
+                </button>
+                <button id="export-btn" class="action-btn secondary-btn">
+                    <span class="btn-text">EXPORT CSV</span>
+                    <span class="btn-glow"></span>
+                </button>
+            </div>
+        </section>
+
+        <!-- Peta Interaktif & Main Stats -->
+        <section class="map-and-stats">
+            <!-- Peta Leaflet.js -->
+            <div class="panel map-panel">
+                <h2 class="panel-title">JAKARTA SPATIAL REALTIME MAP</h2>
+                <div class="map-container">
+                    <div id="map"></div>
+                </div>
+            </div>
+
+            <!-- Stats Real-Time -->
+            <div class="stats-row">
+                <div class="panel stat-card text-glow">
+                    <span class="card-label">TOTAL FORECAST VOLUME</span>
+                    <span id="stat-total-volume" class="card-value">0.00 <span class="unit">Tons</span></span>
+                    <span class="card-meta" id="stat-period-meta">Period: N/A</span>
+                </div>
+                <div class="panel stat-card">
+                    <span class="card-label">RISK STATUS</span>
+                    <span id="stat-risk-status" class="card-value status-badge safe">SAFE</span>
+                    <span class="card-meta" id="stat-location-meta">JIS (Radius 1.5 km)</span>
+                </div>
+                <div class="panel stat-card">
+                    <span class="card-label">RECOMMENDED FLEET</span>
+                    <span id="stat-trucks" class="card-value">0 <span class="unit">Trucks (5T)</span></span>
+                    <span class="card-meta">Logistics Fleet Suggestion</span>
+                </div>
+            </div>
+        </section>
+
+        <!-- Rincian Logistik & Analisis -->
+        <section class="analysis-panel">
+            <!-- Kategori / Komposisi Sampah -->
+            <div class="panel category-panel">
+                <h2 class="panel-title">WASTE COMPOSITION</h2>
+                <div class="progress-container">
+                    <div class="progress-item">
+                        <div class="progress-header">
+                            <span>Organic / Sisa Makanan (49.87%)</span>
+                            <span id="val-organic">0.00 Ton</span>
+                        </div>
+                        <div class="progress-bar-bg">
+                            <div id="bar-organic" class="progress-bar-fill organic" style="width: 0%;"></div>
+                        </div>
+                    </div>
+                    <div class="progress-item">
+                        <div class="progress-header">
+                            <span>Plastic / Plastik (22.95%)</span>
+                            <span id="val-plastic">0.00 Ton</span>
+                        </div>
+                        <div class="progress-bar-bg">
+                            <div id="bar-plastic" class="progress-bar-fill plastic" style="width: 0%;"></div>
+                        </div>
+                    </div>
+                </div>
+            </div>
+
+            <!-- Widget Cuaca Live & Info Event -->
+            <div class="panel weather-event-panel">
+                <h2 class="panel-title">WEATHER & EVENT FORECAST</h2>
+                <div class="weather-grid">
+                    <div class="weather-info">
+                        <span class="weather-temp" id="weather-forecast-text">Fetching Live...</span>
+                        <span class="weather-label" id="weather-location-text">Jakarta, Indonesia</span>
+                    </div>
+                    <div class="weather-details">
+                        <div>Precipitation (Rain): <span id="weather-precip" class="highlight">0.0 mm</span></div>
+                        <div>BMKG Alert: <span id="weather-alert" class="highlight">None</span></div>
+                    </div>
+                </div>
+                <div class="event-box" id="event-box">
+                    <span class="event-title">Upcoming Event Calendar</span>
+                    <p class="event-desc" id="event-desc-text">No major events registered for today.</p>
+                </div>
+            </div>
+
+            <!-- Logistics Plan -->
+            <div class="panel logistics-panel">
+                <h2 class="panel-title">OPERATIONAL LOGISTICS PLAN</h2>
+                <div class="logistics-grid">
+                    <div class="log-item">
+                        <span class="log-label">Manpower Required</span>
+                        <span id="log-manpower" class="log-value">0 Crew</span>
+                    </div>
+                    <div class="log-item">
+                        <span class="log-label">Estimated Collection Time</span>
+                        <span id="log-duration" class="log-value">0.0 Hours</span>
+                    </div>
+                    <div class="log-item">
+                        <span class="log-label">Operational Efficiency</span>
+                        <span id="log-efficiency" class="log-value">85% (Optimal)</span>
+                    </div>
+                    <div class="log-item">
+                        <span class="log-label">Confidence Score</span>
+                        <span id="log-confidence" class="log-value highlight">92.0%</span>
+                    </div>
+                </div>
+            </div>
+        </section>
+    </main>
+
+    <!-- Timeline Harian -->
+    <section class="container timeline-container">
+        <div class="panel timeline-panel">
+            <h2 class="panel-title">DAILY TIMELINE BREAKDOWN</h2>
+            <div id="timeline-list" class="timeline-list">
+                <!-- Will be dynamically populated -->
+                <div class="empty-timeline">Run a prediction to generate the forecast timeline.</div>
+            </div>
+        </div>
+    </section>
+
+    <!-- Hourly Breakdown (for hourly granularity) -->
+    <section id="hourly-section" class="container hourly-container" style="display: none;">
+        <div class="panel hourly-panel">
+            <h2 class="panel-title">HOURLY DISPATCH RISK HEATMAP</h2>
+            <div class="hourly-grid" id="hourly-grid">
+                <!-- Dynamically populated -->
+            </div>
+        </div>
+    </section>
+
+    <footer>
+        <p>&copy; 2026 Waste Intelligence System - DKI Jakarta Province. Calibrated using DLH & KLHK Statistics.</p>
+    </footer>
+
+    <!-- Scripts -->
+    <script src="/static/app.js"></script>
+</body>
+</html>

static/style.css

@@ -0,0 +1,780 @@
+/* CSS Variables for Theming */
+:root {
+    --bg-void: #02040a;
+    --bg-panel: rgba(6, 10, 22, 0.75);
+    --border-color: rgba(0, 240, 255, 0.12);
+    --border-hover: rgba(0, 240, 255, 0.3);
+    
+    --text-main: #E1E3E8;
+    --text-muted: #8c93a3;
+    
+    /* Neon Colors */
+    --cyan: #00F0FF;
+    --cyan-glow: rgba(0, 240, 255, 0.45);
+    --green: #39FF14;
+    --green-glow: rgba(57, 255, 20, 0.35);
+    --yellow: #FFE600;
+    --yellow-glow: rgba(255, 230, 0, 0.35);
+    --red: #FF0055;
+    --red-glow: rgba(255, 0, 85, 0.45);
+    
+    /* Fonts */
+    --font-display: 'Outfit', 'Space Grotesk', system-ui, sans-serif;
+    --font-body: 'Space Grotesk', system-ui, sans-serif;
+    --font-mono: 'JetBrains Mono', monospace;
+}
+
+/* Base resets */
+* {
+    box-sizing: border-box;
+    margin: 0;
+    padding: 0;
+}
+
+body {
+    background-color: var(--bg-void);
+    color: var(--text-main);
+    font-family: var(--font-body);
+    overflow-x: hidden;
+    min-height: 100vh;
+    display: flex;
+    flex-direction: column;
+}
+
+/* Background Rain Canvas */
+#rain-canvas {
+    position: fixed;
+    top: 0;
+    left: 0;
+    width: 100%;
+    height: 100%;
+    z-index: 0;
+    pointer-events: none;
+    opacity: 0.45;
+}
+
+/* Header */
+header {
+    width: 100%;
+    padding: 1.5rem 2.5rem;
+    background: linear-gradient(to bottom, rgba(2, 4, 10, 0.95) 60%, transparent);
+    display: flex;
+    justify-content: space-between;
+    align-items: center;
+    border-bottom: 1px solid rgba(255, 255, 255, 0.03);
+    z-index: 10;
+    position: relative;
+}
+
+.logo-container {
+    display: flex;
+    align-items: baseline;
+    gap: 10px;
+}
+
+.logo-text {
+    font-family: var(--font-display);
+    font-size: 1.8rem;
+    font-weight: 800;
+    letter-spacing: 2px;
+    background: linear-gradient(135deg, #FFF 40%, var(--cyan) 100%);
+    -webkit-background-clip: text;
+    -webkit-text-fill-color: transparent;
+    text-shadow: 0 0 20px rgba(0, 240, 255, 0.15);
+}
+
+.logo-text .highlight {
+    font-weight: 300;
+    letter-spacing: 0px;
+    color: var(--cyan);
+    margin-left: 4px;
+}
+
+.version-tag {
+    font-family: var(--font-mono);
+    font-size: 0.75rem;
+    color: var(--text-muted);
+    background: rgba(255, 255, 255, 0.05);
+    padding: 2px 8px;
+    border-radius: 4px;
+    border: 1px solid rgba(255, 255, 255, 0.08);
+}
+
+.system-status {
+    display: flex;
+    align-items: center;
+    gap: 8px;
+}
+
+.status-indicator {
+    width: 8px;
+    height: 8px;
+    border-radius: 50%;
+}
+
+.status-indicator.online {
+    background-color: var(--green);
+    box-shadow: 0 0 10px var(--green-glow), 0 0 20px var(--green-glow);
+    animation: pulse-green 2s infinite;
+}
+
+.status-label {
+    font-family: var(--font-mono);
+    font-size: 0.8rem;
+    color: var(--text-muted);
+}
+
+/* Grid Layout */
+.dashboard-grid {
+    display: grid;
+    grid-template-columns: 320px 1fr 340px;
+    gap: 1.5rem;
+    padding: 1.5rem 2.5rem;
+    flex: 1;
+    z-index: 5;
+    position: relative;
+}
+
+@media (max-width: 1200px) {
+    .dashboard-grid {
+        grid-template-columns: 1fr;
+    }
+}
+
+/* Panels */
+.panel {
+    background: var(--bg-panel);
+    border: 1px solid var(--border-color);
+    border-radius: 12px;
+    padding: 1.5rem;
+    backdrop-filter: blur(16px);
+    box-shadow: 0 8px 32px 0 rgba(0, 0, 0, 0.37);
+    transition: border-color 0.3s, box-shadow 0.3s;
+}
+
+.panel:hover {
+    border-color: var(--border-hover);
+    box-shadow: 0 8px 32px 0 rgba(0, 240, 255, 0.05);
+}
+
+.panel-title {
+    font-family: var(--font-display);
+    font-size: 0.95rem;
+    font-weight: 600;
+    letter-spacing: 1.5px;
+    color: var(--text-main);
+    margin-bottom: 1.2rem;
+    border-left: 3px solid var(--cyan);
+    padding-left: 8px;
+    text-transform: uppercase;
+}
+
+.panel-subtitle {
+    font-family: var(--font-display);
+    font-size: 0.85rem;
+    font-weight: 600;
+    color: var(--cyan);
+    margin-bottom: 1rem;
+    text-transform: uppercase;
+}
+
+/* Controls */
+.control-group {
+    margin-bottom: 1.2rem;
+}
+
+.control-group label {
+    display: block;
+    font-size: 0.8rem;
+    color: var(--text-muted);
+    margin-bottom: 6px;
+    text-transform: uppercase;
+    font-family: var(--font-mono);
+}
+
+.form-control {
+    width: 100%;
+    background: rgba(0, 0, 0, 0.4);
+    border: 1px solid var(--border-color);
+    color: var(--text-main);
+    padding: 10px 14px;
+    border-radius: 8px;
+    outline: none;
+    font-family: var(--font-body);
+    font-size: 0.9rem;
+    transition: border-color 0.3s;
+}
+
+.form-control:focus {
+    border-color: var(--cyan);
+}
+
+.slider {
+    width: 100%;
+    -webkit-appearance: none;
+    height: 6px;
+    border-radius: 3px;
+    background: rgba(255, 255, 255, 0.1);
+    outline: none;
+}
+
+.slider::-webkit-slider-thumb {
+    -webkit-appearance: none;
+    width: 16px;
+    height: 16px;
+    border-radius: 50%;
+    background: var(--cyan);
+    box-shadow: 0 0 10px var(--cyan-glow);
+    cursor: pointer;
+    transition: transform 0.1s;
+}
+
+.slider::-webkit-slider-thumb:hover {
+    transform: scale(1.25);
+}
+
+.value-display, .override-display {
+    font-family: var(--font-mono);
+    color: var(--cyan);
+    font-weight: bold;
+    float: right;
+}
+
+.range-override-container {
+    display: flex;
+    flex-direction: column;
+    gap: 5px;
+}
+
+.divider {
+    height: 1px;
+    background: rgba(255, 255, 255, 0.05);
+    margin: 1.5rem 0;
+}
+
+/* Buttons */
+.action-btn {
+    width: 100%;
+    padding: 12px;
+    background: rgba(0, 240, 255, 0.06);
+    border: 1px solid var(--cyan);
+    color: var(--cyan);
+    font-family: var(--font-mono);
+    font-size: 0.90rem;
+    font-weight: bold;
+    border-radius: 8px;
+    cursor: pointer;
+    position: relative;
+    overflow: hidden;
+    transition: background 0.3s, box-shadow 0.3s;
+}
+
+.action-btn:hover {
+    background: rgba(0, 240, 255, 0.15);
+    box-shadow: 0 0 20px var(--cyan-glow);
+}
+
+/* Map Panel with Leaflet Map */
+.map-panel {
+    display: flex;
+    flex-direction: column;
+    height: 380px;
+    margin-bottom: 1.5rem;
+}
+
+.map-container {
+    flex: 1;
+    position: relative;
+    background: rgba(0, 0, 0, 0.3);
+    border-radius: 8px;
+    overflow: hidden;
+    border: 1px solid var(--border-color);
+}
+
+#map {
+    width: 100%;
+    height: 100%;
+    background: var(--bg-void) !important;
+}
+
+/* Custom Marker Styling for Leaflet */
+.leaflet-custom-marker {
+    position: relative;
+    cursor: pointer;
+}
+
+.leaflet-custom-marker .marker-pulse {
+    position: absolute;
+    top: 50%;
+    left: 50%;
+    width: 28px;
+    height: 28px;
+    margin-left: -14px;
+    margin-top: -14px;
+    background: var(--cyan);
+    border-radius: 50%;
+    opacity: 0.15;
+    transform: scale(1);
+    animation: pulse-node 2s infinite;
+    pointer-events: none;
+}
+
+.leaflet-custom-marker .marker-core {
+    position: absolute;
+    top: 50%;
+    left: 50%;
+    width: 12px;
+    height: 12px;
+    margin-left: -6px;
+    margin-top: -6px;
+    background: var(--cyan);
+    border: 2px solid #FFF;
+    border-radius: 50%;
+    box-shadow: 0 0 10px var(--cyan-glow);
+    transition: transform 0.2s, background 0.3s;
+}
+
+.leaflet-custom-marker .marker-label {
+    position: absolute;
+    top: -24px;
+    left: 50%;
+    transform: translateX(-50%);
+    font-family: var(--font-mono);
+    font-size: 10px;
+    font-weight: bold;
+    color: var(--text-muted);
+    background: rgba(0, 0, 0, 0.85);
+    padding: 2px 6px;
+    border-radius: 4px;
+    border: 1px solid rgba(255, 255, 255, 0.15);
+    white-space: nowrap;
+    pointer-events: none;
+    transition: color 0.3s, border-color 0.3s;
+}
+
+/* Hover and Active State */
+.leaflet-custom-marker:hover .marker-core {
+    transform: scale(1.2);
+}
+
+.leaflet-custom-marker.active .marker-core {
+    transform: scale(1.3);
+    background: var(--cyan);
+    box-shadow: 0 0 15px var(--cyan), 0 0 25px var(--cyan-glow);
+}
+
+.leaflet-custom-marker.active .marker-label {
+    color: var(--cyan);
+    border-color: var(--cyan);
+    box-shadow: 0 0 10px rgba(0, 240, 255, 0.2);
+}
+
+/* Risk indicator classes for Leaflet Markers */
+.leaflet-custom-marker.safe .marker-core {
+    background: var(--green);
+    box-shadow: 0 0 10px var(--green-glow);
+}
+.leaflet-custom-marker.safe .marker-pulse {
+    background: var(--green);
+}
+
+.leaflet-custom-marker.warning .marker-core {
+    background: var(--yellow);
+    box-shadow: 0 0 10px var(--yellow-glow);
+}
+.leaflet-custom-marker.warning .marker-pulse {
+    background: var(--yellow);
+}
+
+.leaflet-custom-marker.critical .marker-core {
+    background: var(--red);
+    box-shadow: 0 0 10px var(--red-glow);
+}
+.leaflet-custom-marker.critical .marker-pulse {
+    background: var(--red);
+}
+
+/* Leaflet Layout UI Overrides */
+.leaflet-bar {
+    border: 1px solid var(--border-color) !important;
+    border-radius: 8px !important;
+    overflow: hidden;
+    box-shadow: 0 4px 16px rgba(0, 0, 0, 0.6) !important;
+}
+
+.leaflet-bar a {
+    background-color: rgba(6, 10, 22, 0.85) !important;
+    color: var(--text-main) !important;
+    border-bottom: 1px solid var(--border-color) !important;
+    transition: background-color 0.2s, color 0.2s;
+}
+
+.leaflet-bar a:hover {
+    background-color: rgba(0, 240, 255, 0.15) !important;
+    color: var(--cyan) !important;
+}
+
+.leaflet-container {
+    background: var(--bg-void) !important;
+}
+
+/* Stats Cards */
+.stats-row {
+    display: grid;
+    grid-template-columns: repeat(3, 1fr);
+    gap: 1.5rem;
+}
+
+.stat-card {
+    display: flex;
+    flex-direction: column;
+    justify-content: center;
+    padding: 1.2rem;
+    height: 100px;
+}
+
+.card-label {
+    font-family: var(--font-mono);
+    font-size: 0.7rem;
+    color: var(--text-muted);
+    margin-bottom: 6px;
+    text-transform: uppercase;
+}
+
+.card-value {
+    font-family: var(--font-display);
+    font-size: 1.5rem;
+    font-weight: 800;
+    color: #FFF;
+}
+
+.card-value .unit {
+    font-size: 0.85rem;
+    font-weight: 400;
+    color: var(--text-muted);
+}
+
+.status-badge {
+    display: inline-block;
+    padding: 4px 12px;
+    border-radius: 6px;
+    font-size: 0.95rem;
+    font-weight: bold;
+    text-align: center;
+    width: fit-content;
+}
+
+.status-badge.safe {
+    background: rgba(57, 255, 20, 0.08);
+    border: 1px solid var(--green);
+    color: var(--green);
+    text-shadow: 0 0 10px var(--green-glow);
+}
+
+.status-badge.warning {
+    background: rgba(255, 230, 0, 0.08);
+    border: 1px solid var(--yellow);
+    color: var(--yellow);
+    text-shadow: 0 0 10px var(--yellow-glow);
+}
+
+.status-badge.critical {
+    background: rgba(255, 0, 85, 0.08);
+    border: 1px solid var(--red);
+    color: var(--red);
+    text-shadow: 0 0 10px var(--red-glow);
+}
+
+/* Composition / Progress bars */
+.progress-item {
+    margin-bottom: 1.2rem;
+}
+
+.progress-header {
+    display: flex;
+    justify-content: space-between;
+    font-size: 0.8rem;
+    color: var(--text-muted);
+    margin-bottom: 6px;
+    font-family: var(--font-mono);
+}
+
+.progress-bar-bg {
+    width: 100%;
+    height: 8px;
+    background: rgba(255, 255, 255, 0.05);
+    border-radius: 4px;
+    overflow: hidden;
+}
+
+.progress-bar-fill {
+    height: 100%;
+    border-radius: 4px;
+    width: 0%;
+    transition: width 0.8s cubic-bezier(0.25, 0.8, 0.25, 1);
+}
+
+.progress-bar-fill.organic {
+    background: linear-gradient(to right, #4CAF50, #8BC34A);
+    box-shadow: 0 0 10px rgba(76, 175, 80, 0.3);
+}
+
+.progress-bar-fill.plastic {
+    background: linear-gradient(to right, var(--cyan), #00BCD4);
+    box-shadow: 0 0 10px rgba(0, 240, 255, 0.3);
+}
+
+/* Weather & Event Panel */
+.weather-grid {
+    display: flex;
+    justify-content: space-between;
+    align-items: center;
+    background: rgba(0, 0, 0, 0.25);
+    padding: 12px;
+    border-radius: 8px;
+    border: 1px solid rgba(255, 255, 255, 0.03);
+    margin-bottom: 1rem;
+}
+
+.weather-temp {
+    font-family: var(--font-display);
+    font-size: 1.2rem;
+    font-weight: 700;
+    color: #FFF;
+}
+
+.weather-label {
+    display: block;
+    font-size: 0.75rem;
+    color: var(--text-muted);
+}
+
+.weather-details {
+    font-family: var(--font-mono);
+    font-size: 0.75rem;
+    text-align: right;
+    line-height: 1.4;
+}
+
+.weather-details .highlight {
+    color: var(--cyan);
+}
+
+.event-box {
+    padding: 10px;
+    background: rgba(255, 230, 0, 0.03);
+    border-left: 3px solid var(--yellow);
+    border-radius: 0 6px 6px 0;
+}
+
+.event-title {
+    display: block;
+    font-size: 0.75rem;
+    font-weight: bold;
+    color: var(--yellow);
+    font-family: var(--font-mono);
+    margin-bottom: 4px;
+}
+
+.event-desc {
+    font-size: 0.8rem;
+    color: var(--text-main);
+}
+
+/* Logistics Grid */
+.logistics-grid {
+    display: grid;
+    grid-template-columns: 1fr 1fr;
+    gap: 12px;
+}
+
+.log-item {
+    background: rgba(0, 0, 0, 0.2);
+    border: 1px solid rgba(255, 255, 255, 0.03);
+    border-radius: 8px;
+    padding: 10px;
+    display: flex;
+    flex-direction: column;
+}
+
+.log-label {
+    font-family: var(--font-mono);
+    font-size: 0.65rem;
+    color: var(--text-muted);
+    text-transform: uppercase;
+    margin-bottom: 4px;
+}
+
+.log-value {
+    font-size: 0.95rem;
+    font-weight: bold;
+    color: #FFF;
+}
+
+.log-value.highlight {
+    color: var(--cyan);
+    text-shadow: 0 0 10px var(--cyan-glow);
+}
+
+/* Timeline Container */
+.timeline-container {
+    margin-top: 1.5rem;
+    padding: 0 2.5rem;
+    z-index: 5;
+    position: relative;
+}
+
+.timeline-list {
+    display: flex;
+    gap: 12px;
+    overflow-x: auto;
+    padding-bottom: 10px;
+}
+
+.timeline-card {
+    min-width: 140px;
+    background: rgba(0, 0, 0, 0.4);
+    border: 1px solid var(--border-color);
+    border-radius: 8px;
+    padding: 12px;
+    display: flex;
+    flex-direction: column;
+    align-items: center;
+    text-align: center;
+    transition: transform 0.2s, border-color 0.2s;
+}
+
+.timeline-card:hover {
+    transform: translateY(-4px);
+    border-color: var(--cyan);
+}
+
+.timeline-date {
+    font-family: var(--font-mono);
+    font-size: 0.7rem;
+    color: var(--text-muted);
+    margin-bottom: 6px;
+}
+
+.timeline-vol {
+    font-family: var(--font-display);
+    font-size: 1.1rem;
+    font-weight: bold;
+    color: #FFF;
+    margin-bottom: 6px;
+}
+
+.timeline-status {
+    font-size: 0.7rem;
+    padding: 2px 8px;
+    border-radius: 4px;
+    font-weight: bold;
+}
+
+.timeline-status.safe { background: rgba(57, 255, 20, 0.1); color: var(--green); }
+.timeline-status.warning { background: rgba(255, 230, 0, 0.1); color: var(--yellow); }
+.timeline-status.critical { background: rgba(255, 0, 85, 0.1); color: var(--red); }
+
+.empty-timeline {
+    width: 100%;
+    text-align: center;
+    padding: 2rem;
+    color: var(--text-muted);
+    font-style: italic;
+    font-size: 0.9rem;
+}
+
+/* Hourly Breakdown Container */
+.hourly-container {
+    margin-top: 1.5rem;
+    padding: 0 2.5rem;
+    z-index: 5;
+    position: relative;
+    margin-bottom: 2rem;
+}
+
+.hourly-grid {
+    display: grid;
+    grid-template-columns: repeat(24, 1fr);
+    gap: 4px;
+    background: rgba(0, 0, 0, 0.3);
+    padding: 10px;
+    border-radius: 8px;
+    overflow-x: auto;
+}
+
+.hourly-cell {
+    display: flex;
+    flex-direction: column;
+    align-items: center;
+    gap: 4px;
+}
+
+.cell-block {
+    width: 100%;
+    height: 40px;
+    border-radius: 4px;
+    transition: opacity 0.3s;
+}
+
+.cell-block.low { background-color: rgba(57, 255, 20, 0.35); border: 1px solid var(--green); }
+.cell-block.medium { background-color: rgba(255, 230, 0, 0.35); border: 1px solid var(--yellow); }
+.cell-block.high { background-color: rgba(255, 0, 85, 0.35); border: 1px solid var(--red); }
+
+.cell-time {
+    font-family: var(--font-mono);
+    font-size: 8px;
+    color: var(--text-muted);
+}
+
+/* Footer */
+footer {
+    width: 100%;
+    padding: 1.5rem;
+    text-align: center;
+    border-top: 1px solid rgba(255, 255, 255, 0.03);
+    color: var(--text-muted);
+    font-size: 0.75rem;
+    font-family: var(--font-mono);
+    margin-top: auto;
+}
+
+/* Animations */
+@keyframes pulse-green {
+    0% { box-shadow: 0 0 0 0 rgba(57, 255, 20, 0.4); }
+    70% { box-shadow: 0 0 0 8px rgba(57, 255, 20, 0); }
+    100% { box-shadow: 0 0 0 0 rgba(57, 255, 20, 0); }
+}
+
+@keyframes pulse-node {
+    0% { transform: scale(0.9); opacity: 0.35; }
+    70% { transform: scale(1.6); opacity: 0; }
+    100% { transform: scale(0.9); opacity: 0; }
+}
+
+.card-meta {
+    font-family: var(--font-mono);
+    font-size: 0.65rem;
+    color: var(--text-muted);
+    margin-top: 6px;
+    display: block;
+    text-transform: uppercase;
+}
+
+.button-row {
+    display: grid;
+    grid-template-columns: 1fr 1fr;
+    gap: 10px;
+}
+
+.secondary-btn {
+    background: rgba(57, 255, 20, 0.04) !important;
+    border: 1px solid var(--green) !important;
+    color: var(--green) !important;
+}
+
+.secondary-btn:hover {
+    background: rgba(57, 255, 20, 0.12) !important;
+    box-shadow: 0 0 20px var(--green-glow) !important;
+}
+

train.py

@@ -3,119 +3,90 @@ import numpy as np
 from sklearn.ensemble import GradientBoostingRegressor
 from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score
 import joblib
-import io
 import warnings
 warnings.filterwarnings('ignore')
 
-print("🚀 MEMULAI PROSES TRAINING AI LEVEL ADVANCED (ECO-TWIN PRO)...\n")
+print("MEMULAI PROSES TRAINING AI LEVEL PRODUCTION (LOCALIZED, LAG WEATHER & HOLIDAYS)...\n")
 
 # ==========================================
-# 1. DATA INGESTION & AUGMENTATION (2 TAHUN)
+# 1. LOAD LOCALIZED DATA
 # ==========================================
-print("📥 1. Menarik & Memproses Data Historis (2023 - 2024)...")
-
-# Baseline Sampah (Diambil dari SIPSN DKI 2025)
-base_sampah = 1050.50 
-mrt_harian_avg = 85000 
-hujan_mean = 10.5
-
-# Data Event 
-data_event_csv = """Tanggal,Nama_Event,Ada_Event
-2023-01-01,Tahun Baru 2023,1
-2023-03-11,Konser BLACKPINK,1
-2023-03-12,Konser BLACKPINK,1
-2023-05-26,Java Jazz,1
-2023-06-19,Timnas Argentina,1
-2023-11-15,Coldplay,1
-2023-12-31,Tahun Baru 2024,1
-2024-01-01,Tahun Baru 2024,1
-2024-03-02,Ed Sheeran,1
-2024-05-24,Java Jazz 2024,1
-2024-12-31,Malam Tahun Baru 2025,1"""
-df_event = pd.read_csv(io.StringIO(data_event_csv))
-df_event['Tanggal'] = pd.to_datetime(df_event['Tanggal'])
-
-# Bikin Master Kalender 2 Tahun (Lebih banyak data, AI makin pintar)
-df = pd.DataFrame({'Tanggal': pd.date_range(start="2023-01-01", end="2024-12-31")})
-df = pd.merge(df, df_event[['Tanggal', 'Ada_Event']], on='Tanggal', how='left').fillna({'Ada_Event': 0})
-
-# Simulasi Pola Realistis
-df['Penumpang_MRT'] = np.random.normal(loc=mrt_harian_avg, scale=mrt_harian_avg*0.15, size=len(df)).astype(int)
-df['Curah_Hujan_mm'] = np.random.exponential(scale=hujan_mean, size=len(df))
-df.loc[df['Curah_Hujan_mm'] < 2, 'Curah_Hujan_mm'] = 0
+print("1. Menarik & Memproses Data Historis Lokal...")
+df = pd.read_csv('dataset_local_2026.csv')
+df['Tanggal'] = pd.to_datetime(df['Tanggal'])
+
+# Sort chronologically to maintain time order
+df = df.sort_values(['Tanggal', 'Location']).reset_index(drop=True)
 
 # ==========================================
-# 2. ADVANCED FEATURE ENGINEERING (MIND-BLOWING)
+# 2. FEATURE ENGINEERING (LOCAL BINDING)
 # ==========================================
-print("🧠 2. Melakukan Feature Engineering (Ekstraksi Pola Waktu)...")
-
-# Ekstraksi Siklus Waktu
-df['Hari_Dalam_Minggu'] = df['Tanggal'].dt.dayofweek # 0=Senin, 6=Minggu
-df['Bulan'] = df['Tanggal'].dt.month
-df['Is_Weekend'] = df['Hari_Dalam_Minggu'].apply(lambda x: 1 if x >= 5 else 0)
-
-# Lag Features (Mengingat masa lalu)
-# "Hujan kemarin bikin sampah hari ini lebih berat (menyerap air)"
-df['Hujan_Kemarin'] = df['Curah_Hujan_mm'].shift(1).fillna(0)
+print("2. Melakukan One-Hot Encoding Lokasi & Verifikasi Fitur...")
 
-# Target Variable Generation (Rumus Super Kompleks)
-df['Volume_Sampah_Ton'] = base_sampah + \
-    (df['Ada_Event'] * base_sampah * np.random.uniform(0.15, 0.30, size=len(df))) + \
-    (df['Is_Weekend'] * base_sampah * 0.08) + \
-    (df['Curah_Hujan_mm'] / 50 * base_sampah * 0.03) + \
-    (df['Hujan_Kemarin'] / 50 * base_sampah * 0.05) + \
-    ((df['Penumpang_MRT'] - mrt_harian_avg) / mrt_harian_avg * base_sampah * 0.02)
+# Defensive manual one-hot encoding to guarantee column names and order
+locations = ['JIS', 'GBK', 'Pasar Senen', 'Gang Sempit Tambora']
+for loc in locations:
+    df[f'Loc_{loc}'] = (df['Location'] == loc).astype(int)
 
-# Noise (Fluktuasi harian)
-df['Volume_Sampah_Ton'] += np.random.normal(0, base_sampah*0.02, size=len(df))
-df['Volume_Sampah_Ton'] = df['Volume_Sampah_Ton'].round(2)
+# Fitur yang dipakai AI buat berpikir
+fitur = [
+    'Loc_JIS', 'Loc_GBK', 'Loc_Pasar Senen', 'Loc_Gang Sempit Tambora',
+    'RR', 'Rain_Lag_1', 'Rain_Lag_2', 'Is_Holiday', 'Ada_Event', 'Crowd_Scale',
+    'Hari_Ke', 'Is_Weekend', 'Hari_Dalam_Minggu', 'Bulan'
+]
 
-# Simpan dataset
-df.to_csv('dataset_advanced_eco_twin.csv', index=False)
+X = df[fitur]
+y = df['Volume_Ton']
 
 # ==========================================
 # 3. CHRONOLOGICAL SPLIT & TRAINING
 # ==========================================
-print("⚙️ 3. Melatih Model AI dengan Algoritma Gradient Boosting...")
+print("3. Membagi Data secara Kronologis (75/25) & Melatih Model...")
 
-# Fitur yang dipakai AI buat mikir
-fitur = ['Penumpang_MRT', 'Ada_Event', 'Curah_Hujan_mm', 'Hujan_Kemarin', 'Hari_Dalam_Minggu', 'Bulan', 'Is_Weekend']
-X = df[fitur]
-y = df['Volume_Sampah_Ton']
+# 75% days for training, 25% for test. 
+# Since we have 4 locations per day, we split at index: (len(df) // 4 * 0.75) * 4
+num_days = len(df) // 4
+train_days = int(num_days * 0.75)
+train_size = train_days * 4
 
-# Memisahkan masa lalu (2023) buat belajar, masa depan (2024) buat ujian
-train_size = int(len(df) * 0.75) # 75% data awal
 X_train, X_test = X.iloc[:train_size], X.iloc[train_size:]
 y_train, y_test = y.iloc[:train_size], y.iloc[train_size:]
 
-# Menggunakan Gradient Boosting (State-of-the-Art)
+# Menggunakan Gradient Boosting Regressor (Optimasi Parameter untuk Akurasi >90%)
 model = GradientBoostingRegressor(
-    n_estimators=200, 
-    learning_rate=0.1, 
-    max_depth=4, 
+    n_estimators=300, 
+    learning_rate=0.05, 
+    max_depth=5, 
     random_state=42
 )
 model.fit(X_train, y_train)
 
 # ==========================================
-# 4. EVALUASI AKURASI (BUAT DIPAMERIN KE JURI)
+# 4. EVALUASI AKURASI
 # ==========================================
+print("4. Mengevaluasi Performa Model pada Data Pengujian...")
 prediksi = model.predict(X_test)
 rmse = mean_squared_error(y_test, prediksi) ** 0.5
 mae = mean_absolute_error(y_test, prediksi)
 r2 = r2_score(y_test, prediksi)
 
-print("\n📊 HASIL EVALUASI MODEL (METRICS):")
-print(f"   ✅ Root Mean Squared Error (RMSE) : {rmse:.2f} Ton")
-print(f"   ✅ Mean Absolute Error (MAE)      : {mae:.2f} Ton")
-print(f"   ✅ R-Squared (R2 Score)           : {r2 * 100:.2f}% (Tingkat Kepercayaan AI)")
+# Hitung Mean Absolute Percentage Error (MAPE)
+mape = np.mean(np.abs((y_test - prediksi) / y_test)) * 100
+akurasi = 100 - mape
+
+print("\nHASIL EVALUASI MODEL (METRICS):")
+print(f"   Root Mean Squared Error (RMSE) : {rmse:.2f} Ton")
+print(f"   Mean Absolute Error (MAE)      : {mae:.2f} Ton")
+print(f"   R-Squared (R2 Score)           : {r2 * 100:.2f}% (Tingkat Kepercayaan AI)")
+print(f"   Mean Absolute Percentage Error (MAPE) : {mape:.2f}%")
+print(f"   Akurasi Prediksi Sampah        : {akurasi:.2f}%")
 
 # Cek Fitur Paling Berpengaruh
 importances = model.feature_importances_
-print("\n🌟 FITUR PALING BERPENGARUH PADA TIMBULAN SAMPAH:")
+print("\nFITUR PALING BERPENGARUH PADA TIMBULAN SAMPAH:")
 for name, importance in zip(fitur, importances):
     print(f"   - {name}: {importance*100:.1f}%")
 
 # Simpan Model
 joblib.dump(model, 'model_sampah_advanced.pkl')
-print("\n💾 SUCCESS! 'model_sampah_advanced.pkl' berhasil di-generate!")
+print("\nSUCCESS! 'model_sampah_advanced.pkl' berhasil di-generate!")