# Aeterna AI - Front-End API Integration Guide (v4.0.0) Dokumen ini ditujukan bagi tim Front-End untuk mengintegrasikan antarmuka pengguna dengan backend **Aeterna AI (Waste Intelligence Platform)**. --- ## πŸ“‘ Konfigurasi Global * **Base URL (Local)**: `http://localhost:8001` * **Content-Type**: `application/json` * **CORS**: Diaktifkan secara wildcard (`*`) untuk semua origin, method, dan header. --- ## πŸ—ΊοΈ Konstanta Wilayah (44 Kecamatan DKI Jakarta) Untuk memetakan wilayah pada leaflet/map atau drop-down pilihan di FE, gunakan konstanta koordinat dan baseline berikut: ```typescript export interface RegionMetadata { latitude: number; longitude: number; normal_avg: number; warning_threshold: number; critical_threshold: number; city: 'Jakarta Pusat' | 'Jakarta Utara' | 'Jakarta Barat' | 'Jakarta Selatan' | 'Jakarta Timur' | 'Kepulauan Seribu'; } export const KECAMATAN_DATABASE: Record = { // JAKARTA PUSAT "Menteng": { latitude: -6.1950, longitude: 106.8322, normal_avg: 120.0, warning_threshold: 160.0, critical_threshold: 180.0, city: "Jakarta Pusat" }, "Senen": { latitude: -6.1822, longitude: 106.8452, normal_avg: 180.0, warning_threshold: 220.0, critical_threshold: 240.0, city: "Jakarta Pusat" }, "Cempaka Putih": { latitude: -6.1802, longitude: 106.8686, normal_avg: 90.0, warning_threshold: 120.0, critical_threshold: 140.0, city: "Jakarta Pusat" }, "Johar Baru": { latitude: -6.1866, longitude: 106.8572, normal_avg: 70.0, warning_threshold: 95.0, critical_threshold: 110.0, city: "Jakarta Pusat" }, "Kemayoran": { latitude: -6.1628, longitude: 106.8438, normal_avg: 180.0, warning_threshold: 220.0, critical_threshold: 240.0, city: "Jakarta Pusat" }, "Sawah Besar": { latitude: -6.1554, longitude: 106.8322, normal_avg: 110.0, warning_threshold: 145.0, critical_threshold: 165.0, city: "Jakarta Pusat" }, "Tanah Abang": { latitude: -6.2104, longitude: 106.8122, normal_avg: 250.0, warning_threshold: 320.0, critical_threshold: 350.0, city: "Jakarta Pusat" }, "Gambir": { latitude: -6.1764, longitude: 106.8190, normal_avg: 150.0, warning_threshold: 195.0, critical_threshold: 215.0, city: "Jakarta Pusat" }, // JAKARTA UTARA "Penjaringan": { latitude: -6.1264, longitude: 106.7822, normal_avg: 280.0, warning_threshold: 350.0, critical_threshold: 380.0, city: "Jakarta Utara" }, "Tanjung Priok": { latitude: -6.1322, longitude: 106.8722, normal_avg: 260.0, warning_threshold: 320.0, critical_threshold: 350.0, city: "Jakarta Utara" }, "Koja": { latitude: -6.1214, longitude: 106.9133, normal_avg: 190.0, warning_threshold: 240.0, critical_threshold: 270.0, city: "Jakarta Utara" }, "Cilincing": { latitude: -6.1288, longitude: 106.9452, normal_avg: 290.0, warning_threshold: 370.0, critical_threshold: 400.0, city: "Jakarta Utara" }, "Pademangan": { latitude: -6.1328, longitude: 106.8422, normal_avg: 140.0, warning_threshold: 180.0, critical_threshold: 200.0, city: "Jakarta Utara" }, "Kelapa Gading": { latitude: -6.1552, longitude: 106.9022, normal_avg: 190.0, warning_threshold: 240.0, critical_threshold: 270.0, city: "Jakarta Utara" }, // JAKARTA BARAT "Cengkareng": { latitude: -6.1528, longitude: 106.7322, normal_avg: 340.0, warning_threshold: 420.0, critical_threshold: 460.0, city: "Jakarta Barat" }, "Grogol Petamburan": { latitude: -6.1622, longitude: 106.7882, normal_avg: 220.0, warning_threshold: 280.0, critical_threshold: 310.0, city: "Jakarta Barat" }, "Kalideres": { latitude: -6.1428, longitude: 106.7022, normal_avg: 260.0, warning_threshold: 330.0, critical_threshold: 360.0, city: "Jakarta Barat" }, "Kebon Jeruk": { latitude: -6.1922, longitude: 106.7722, normal_avg: 210.0, warning_threshold: 260.0, critical_threshold: 290.0, city: "Jakarta Barat" }, "Kembangan": { latitude: -6.1828, longitude: 106.7382, normal_avg: 180.0, warning_threshold: 230.0, critical_threshold: 250.0, city: "Jakarta Barat" }, "Palmerah": { latitude: -6.2028, longitude: 106.7882, normal_avg: 160.0, warning_threshold: 200.0, critical_threshold: 220.0, city: "Jakarta Barat" }, "Taman Sari": { latitude: -6.1454, longitude: 106.8182, normal_avg: 100.0, warning_threshold: 130.0, critical_threshold: 150.0, city: "Jakarta Barat" }, "Tambora": { latitude: -6.1500, longitude: 106.8000, normal_avg: 80.0, warning_threshold: 110.0, critical_threshold: 125.0, city: "Jakarta Barat" }, // JAKARTA SELATAN "Cilandak": { latitude: -6.2928, longitude: 106.7922, normal_avg: 180.0, warning_threshold: 230.0, critical_threshold: 250.0, city: "Jakarta Selatan" }, "Jagakarsa": { latitude: -6.3328, longitude: 106.8222, normal_avg: 220.0, warning_threshold: 280.0, critical_threshold: 310.0, city: "Jakarta Selatan" }, "Kebayoran Baru": { latitude: -6.2422, longitude: 106.7982, normal_avg: 210.0, warning_threshold: 260.0, critical_threshold: 290.0, city: "Jakarta Selatan" }, "Kebayoran Lama": { latitude: -6.2488, longitude: 106.7722, normal_avg: 230.0, warning_threshold: 290.0, critical_threshold: 320.0, city: "Jakarta Selatan" }, "Mampang Prapatan": { latitude: -6.2522, longitude: 106.8182, normal_avg: 120.0, warning_threshold: 150.0, critical_threshold: 170.0, city: "Jakarta Selatan" }, "Pancoran": { latitude: -6.2622, longitude: 106.8382, normal_avg: 130.0, warning_threshold: 160.0, critical_threshold: 180.0, city: "Jakarta Selatan" }, "Pasar Minggu": { latitude: -6.2828, longitude: 106.8438, normal_avg: 240.0, warning_threshold: 300.0, critical_threshold: 330.0, city: "Jakarta Selatan" }, "Pesanggrahan": { latitude: -6.2588, longitude: 106.7588, normal_avg: 160.0, warning_threshold: 200.0, critical_threshold: 220.0, city: "Jakarta Selatan" }, "Setiabudi": { latitude: -6.2228, longitude: 106.8282, normal_avg: 190.0, warning_threshold: 240.0, critical_threshold: 270.0, city: "Jakarta Selatan" }, "Tebet": { latitude: -6.2288, longitude: 106.8482, normal_avg: 170.0, warning_threshold: 210.0, critical_threshold: 230.0, city: "Jakarta Selatan" }, // JAKARTA TIMUR "Cakung": { latitude: -6.1828, longitude: 106.9482, normal_avg: 350.0, warning_threshold: 430.0, critical_threshold: 470.0, city: "Jakarta Timur" }, "Cipayung": { latitude: -6.3128, longitude: 106.9022, normal_avg: 140.0, warning_threshold: 180.0, critical_threshold: 200.0, city: "Jakarta Timur" }, "Ciracas": { latitude: -6.3228, longitude: 106.8782, normal_avg: 190.0, warning_threshold: 240.0, critical_threshold: 270.0, city: "Jakarta Timur" }, "Duren Sawit": { latitude: -6.2228, longitude: 106.9282, normal_avg: 300.0, warning_threshold: 370.0, critical_threshold: 410.0, city: "Jakarta Timur" }, "Jatinegara": { latitude: -6.2222, longitude: 106.8682, normal_avg: 240.0, warning_threshold: 300.0, critical_threshold: 330.0, city: "Jakarta Timur" }, "Kramat Jati": { latitude: -6.2722, longitude: 106.8682, normal_avg: 220.0, warning_threshold: 270.0, critical_threshold: 300.0, city: "Jakarta Timur" }, "Makasar": { latitude: -6.2622, longitude: 106.8782, normal_avg: 160.0, warning_threshold: 200.0, critical_threshold: 220.0, city: "Jakarta Timur" }, "Matraman": { latitude: -6.2022, longitude: 106.8582, normal_avg: 130.0, warning_threshold: 160.0, critical_threshold: 180.0, city: "Jakarta Timur" }, "Pasar Rebo": { latitude: -6.3122, longitude: 106.8522, normal_avg: 150.0, warning_threshold: 190.0, critical_threshold: 210.0, city: "Jakarta Timur" }, "Pulo Gadung": { latitude: -6.1922, longitude: 106.8922, normal_avg: 220.0, warning_threshold: 270.0, critical_threshold: 300.0, city: "Jakarta Timur" }, // KEPULAUAN SERIBU "Kepulauan Seribu Utara": { latitude: -5.5722, longitude: 106.5522, normal_avg: 11.0, warning_threshold: 15.0, critical_threshold: 18.0, city: "Kepulauan Seribu" }, "Kepulauan Seribu Selatan": { latitude: -5.7722, longitude: 106.6522, normal_avg: 9.0, warning_threshold: 12.0, critical_threshold: 15.0, city: "Kepulauan Seribu" } }; ``` --- ## πŸ”Œ Referensi API Endpoint ### 1. Mengambil Berita Ter-crawled Harian Endpoint ini menyajikan database berita seputar persampahan DKI Jakarta yang diperbarui berkala setiap 1 jam. * **URL**: `/api/v1/news` * **Method**: `GET` * **Headers**: `Accept: application/json` * **Response Schema (`200 OK`)**: ```json [ { "title": "DKI Uji Coba Penarikan Retribusi Sampah Pelayanan Kebersihan Harian", "source": "Antara News", "url": "https://www.antaranews.com/tag/sampah-jakarta", "date_fetched": "2026-07-10", "summary": "Pemprov DKI Jakarta merencanakan uji coba penarikan retribusi pelayanan kebersihan/sampah berdasarkan golongan daya listrik..." } ] ``` --- ### 2. Prediksi AI Otonom (Autopilot Mode) Mengambil prediksi otonom untuk ke-44 kecamatan sekaligus untuk hari ini. Berguna untuk dashboard autopilot utama. * **URL**: `/api/v1/autopilot` * **Method**: `GET` * **Response Schema (`200 OK`)**: ```json { "status": "success", "date": "2026-07-10", "total_volume_ton": 8105.42, "total_trucks": 1640, "top_kecamatan": [ { "location": "Cakung", "volume_ton": 355.20, "trucks": 72, "status": "SAFE", "city": "Jakarta Timur" } ], "rainy_regions": 0, "event_today": null } ``` --- ### 3. Simulasi Prediksi Wilayah (Predictor Tool) Melakukan peramalan timbulan sampah untuk kecamatan tertentu dengan parameter simulasi cuaca/event keramaian. * **URL**: `/api/v1/predict` * **Method**: `POST` * **Request Body**: ```typescript interface PredictionRequest { forecast_days: number; // Ambang batas: 1 - 30 hari rainfall_mm: number; // Curah hujan override (0.0 = Auto Open-Meteo) event_scale: number; // 0 (none) sampai 5 (massive crowd) location: string; // Salah satu nama dari 44 kecamatan granularity: 'daily' | 'hourly'; model_type: 'chronos' | 'gradient_boosting'; } ``` * **Contoh Request Payload**: ```json { "forecast_days": 7, "rainfall_mm": 0.0, "event_scale": 0, "location": "Menteng", "granularity": "daily", "model_type": "gradient_boosting" } ``` * **Response Schema (`200 OK`)**: ```json { "status": "success", "message": "Normal conditions.", "confidence_score": 0.9828, "data": { "prediction_results": [ { "date": "2026-07-10", "location": "Menteng", "total_volume_ton": 120.54, "organic_waste_ton": 60.11, "plastic_waste_ton": 27.66, "paper_waste_ton": 13.86, "glass_waste_ton": 3.86, "metal_waste_ton": 2.53, "textile_waste_ton": 5.06, "other_waste_ton": 7.46, "recommended_trucks": 25, "risk_status": "SAFE", "event_info": null, "hourly_breakdown": null } ], "logistics_plan": { "trucks_needed": 25, "manpower": 75, "estimated_duration_hours": 24.1, "efficiency_rate": "85% (Optimal)" } } } ``` --- ### 4. Unduh Berkas CSV Prediksi Mengunduh berkas tabel data hasil simulasi prediksi. * **URL**: `/api/v1/predict/csv` * **Method**: `POST` * **Request Body**: Sama dengan request `/api/v1/predict` * **Response**: Binary Blob (`text/csv` stream file). --- ### 5. Mengambil Peringatan Operasional Dinamis (Alerts) Mendapatkan peringatan kritis wilayah yang volumenya melebihi ambang batas warning/critical. * **URL**: `/api/v1/alerts` * **Method**: `GET` * **Query Parameters**: `location` (opsional, untuk menyaring satu kecamatan) * **Response Schema (`200 OK`)**: ```json { "status": "success", "alert_count": 2, "alerts": [ { "date": "2026-07-10", "location": "Cakung", "status": "WARNING", "estimated_volume_ton": 435.0, "message": "Alert: WARNING volume expected at Cakung" } ], "last_updated": "2026-07-10T20:52:00.123456" } ``` --- ## ⚑ Contoh Integrasi Frontend (Axios / JavaScript) Berikut adalah contoh cara menarik data prediksi Autopilot dan memuatnya ke komponen halaman FE Anda: ```javascript import axios from 'axios'; const BACKEND_URL = 'http://localhost:8001'; // 1. Memuat Umpan Berita AI export async function getWasteNews() { try { const res = await axios.get(`${BACKEND_URL}/api/v1/news`); return res.data; // Mengembalikan array berita } catch (error) { console.error("Gagal menarik berita sampah:", error); return []; } } // 2. Memuat Data Autopilot Otonom DKI export async function getAutopilotData() { try { const res = await axios.get(`${BACKEND_URL}/api/v1/autopilot`); return res.data; } catch (error) { console.error("Gagal memuat autopilot data:", error); return null; } } // 3. Menjalankan Prediksi Manual (Simulation) export async function postSimulationPrediction(kecamatan, hari = 7, model = 'gradient_boosting') { const payload = { forecast_days: hari, rainfall_mm: 0.0, // Auto event_scale: 0, location: kecamatan, granularity: hari <= 7 ? 'hourly' : 'daily', model_type: model }; try { const res = await axios.post(`${BACKEND_URL}/api/v1/predict`, payload); return res.data; } catch (error) { console.error("Gagal melakukan prediksi simulasi:", error); throw error; } } ```