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metadata 
title: AgriSensa API
emoji: 🌾
colorFrom: green
colorTo: yellow
sdk: docker
pinned: false
app_port: 7860

🌾 AgriSensa

Platform Pertanian Cerdas Berbasis AI untuk Petani Indonesia

Python Flask License Hugging Face

Demo • Dokumentasi • Fitur • Instalasi

📖 Tentang AgriSensa

AgriSensa adalah platform pertanian cerdas yang memanfaatkan teknologi Artificial Intelligence (AI), Machine Learning, dan Computer Vision untuk membantu petani Indonesia meningkatkan produktivitas dan keberlanjutan usaha tani. Platform ini menyediakan 25+ modul canggih yang mencakup analisis tanah, rekomendasi tanaman, deteksi penyakit, prediksi harga pasar, dan banyak lagi.

🎯 Visi & Misi

Visi: Menjadi platform pertanian digital terdepan yang memberdayakan petani Indonesia dengan teknologi AI.

Misi:

  • Meningkatkan produktivitas pertanian melalui rekomendasi berbasis data
  • Mengurangi kerugian akibat hama dan penyakit dengan deteksi dini
  • Memberikan akses informasi pasar yang transparan dan real-time
  • Menyediakan edukasi pertanian yang mudah diakses

✨ Fitur Utama

🤖 AI & Machine Learning

  • AgriBot - Asisten pertanian cerdas berbasis Google Gemini AI
  • Rekomendasi Tanaman Cerdas - Analisis NPK, pH, iklim untuk rekomendasi optimal
  • Prediksi Hasil Panen - Estimasi tonase berdasarkan kondisi lahan
  • Analisis Tren Harga - Prediksi harga komoditas dengan Linear Regression
  • Intelijen Prediktif (XAI) - Prediksi dengan penjelasan transparan

🔬 Analisis & Diagnostik

  • Dokter Tanaman AI - Deteksi penyakit tanaman dengan Roboflow AI
  • Analisis BWD - Deteksi penyakit padi dengan Computer Vision
  • Diagnostik Gejala Cerdas - Identifikasi hama & penyakit via kuesioner
  • Analisis NPK Manual - Input dan analisis kesuburan tanah
  • Analis Risiko Keberhasilan - Evaluasi potensi keberhasilan usaha tani

🧮 Kalkulator & Tools

  • Kalkulator Pupuk Holistik - Perhitungan kebutuhan pupuk presisi dengan jadwal bertahap
  • Kalkulator Konversi Pupuk - Konversi dosis antar jenis pupuk
  • Rekomendasi Pupuk - Saran pemupukan berdasarkan kondisi tanah
  • Strategi Penyemprotan Cerdas - Optimasi jadwal dan dosis penyemprotan

💰 Intelijen Pasar

  • Intelijen Harga Pasar - Monitor harga komoditas real-time
  • Analisis Tren Harga - Visualisasi dan prediksi tren harga
  • Katalog Pupuk - Referensi lengkap harga dan spesifikasi pupuk

📚 Basis Pengetahuan

  • Basis Pengetahuan Budidaya - SOP dan teknik budidaya terbaik (20+ komoditas)
  • Ensiklopedia Komoditas - Informasi mendalam berbagai komoditas
  • Panduan Buah - Ensiklopedia budidaya tanaman buah tropis
  • Panduan Hama & Penyakit - Database lengkap hama dan pengendaliannya
  • Info Pestisida - Direktori bahan aktif, cara kerja, dan keamanan
  • Pusat Pengetahuan Pertanian - Info pupuk NPK, agen hayati, hormon tanaman
  • Info pH Tanah - Panduan manajemen keasaman tanah

🗺️ Fitur Lanjutan

  • AgriMap AI - Rekomendasi tanaman berbasis lokasi (Geospatial)
  • Perencana Hasil Panen AI - Perencanaan target panen dengan AI
  • Dasbor Rekomendasi Terpadu - Pusat rekomendasi terintegrasi
  • Pustaka Dokumen - Regulasi dan dokumen resmi pertanian

🏗️ Arsitektur Teknologi

Tech Stack

Backend:

  • Python 3.12
  • Flask 3.0 (Web Framework)
  • SQLAlchemy (ORM)
  • Flask-Migrate (Database Migrations)
  • Flask-JWT-Extended (Authentication)
  • Flask-CORS (Cross-Origin Resource Sharing)
  • Flask-Limiter (Rate Limiting)

Machine Learning & AI:

  • scikit-learn (ML Models)
  • TensorFlow/Keras (Deep Learning)
  • Google Generative AI (Gemini API)
  • Roboflow (Computer Vision)
  • SHAP (Explainable AI)

Data Processing:

  • pandas (Data Manipulation)
  • numpy (Numerical Computing)
  • Pillow (Image Processing)

Frontend:

  • HTML5, CSS3, JavaScript (ES6+)
  • Chart.js (Data Visualization)
  • Marked.js (Markdown Rendering)

Deployment:

  • Docker (Containerization)
  • Hugging Face Spaces (Hosting)
  • Git (Version Control)

Struktur Direktori 

agrisensa-api/
├── app/
│   ├── __init__.py           # Application factory
│   ├── config/               # Configuration files
│   ├── data/                 # Static data & databases
│   │   ├── cultivation_db.py # Cultivation knowledge base
│   │   ├── pest_disease_db.py# Pest & disease database
│   │   └── fertilizer_db.py  # Fertilizer database
│   ├── models/               # SQLAlchemy models
│   ├── routes/               # API routes/blueprints
│   │   ├── main.py          # Main routes
│   │   ├── legacy.py        # Legacy endpoints
│   │   ├── analysis.py      # Analysis endpoints
│   │   └── ...
│   ├── services/             # Business logic
│   │   ├── ml_service.py    # ML model service
│   │   ├── market_service.py# Market intelligence
│   │   ├── chatbot_service.py# Chatbot service
│   │   └── ...
│   └── utils/               # Utility functions
├── templates/               # HTML templates
│   └── modules/            # Module-specific templates
├── static/                 # Static assets
│   ├── css/
│   ├── js/
│   ├── icons/
│   ├── manifest.json       # PWA manifest
│   └── sw.js              # Service worker
├── instance/              # Instance-specific files
├── migrations/            # Database migrations
├── Dockerfile            # Docker configuration
├── requirements.txt      # Python dependencies
├── run.py               # Application entry point
└── README.md            # This file

🚀 Instalasi

Prerequisites

  • Python 3.12+
  • pip (Python package manager)
  • Git
  • (Optional) Docker

Local Development

  1. Clone Repository
git clone https://github.com/yourusername/agrisensa-api.git
cd agrisensa-api
  1. Create Virtual Environment
python -m venv venv

# Windows
venv\Scripts\activate

# Linux/Mac
source venv/bin/activate
  1. Install Dependencies
pip install -r requirements.txt
  1. Set Environment Variables

Create a .env file:

FLASK_ENV=development
SECRET_KEY=your-secret-key-here
DATABASE_URL=sqlite:///agrisensa.db
GEMINI_API_KEY=your-gemini-api-key
  1. Initialize Database
flask init-db
  1. Run Development Server
python run.py

Server akan berjalan di http://localhost:5000

Docker Deployment 

# Build image
docker build -t agrisensa-api .

# Run container
docker run -p 7860:7860 agrisensa-api

Hugging Face Spaces

  1. Fork repository ini
  2. Buat Space baru di Hugging Face
  3. Connect repository ke Space
  4. Set environment variables di Space Settings
  5. Deploy!

📱 Progressive Web App (PWA)

AgriSensa mendukung instalasi sebagai aplikasi Android/iOS melalui PWA:

Cara Install di Android:

  1. Buka AgriSensa di Chrome
  2. Tap menu (⋮) → "Install App" atau "Add to Home Screen"
  3. Aplikasi akan muncul di menu HP Anda

Fitur PWA:

  • ✅ Offline capability
  • ✅ App-like experience
  • ✅ Fast loading
  • ✅ Push notifications (coming soon)

🔌 API Documentation

Base URL 

Production: https://huggingface.co/spaces/yandri918/agrisensa-api
Local: http://localhost:5000

Authentication

Beberapa endpoint memerlukan JWT token. Dapatkan token melalui /api/auth/login.

Key Endpoints

Crop Recommendation 

POST /recommend-crop
Content-Type: application/json

{
  "n_value": 80,
  "p_value": 40,
  "k_value": 50,
  "ph": 6.5,
  "temperature": 28,
  "humidity": 75,
  "rainfall": 150
}

Fertilizer Recommendation 

POST /recommend-fertilizer
Content-Type: application/json

{
  "commodity": "padi",
  "area_sqm": 1000,
  "ph": 6.5
}

Yield Prediction (XAI) 

POST /predict-yield-advanced
Content-Type: application/json

{
  "n": 80,
  "p": 40,
  "k": 50,
  "temperature": 28,
  "humidity": 75,
  "ph": 6.5,
  "rainfall": 150
}

Chatbot 

POST /chat
Content-Type: application/json

{
  "message": "Bagaimana cara menanam padi yang baik?"
}

Market Prices 

GET /get-ticker-prices

Price Trend Prediction 

POST /predict-price-trend
Content-Type: application/json

{
  "commodity": "cabe",
  "days": 7
}

Dokumentasi lengkap tersedia di /api/info

🧪 Testing 

# Run all tests
pytest

# Run with coverage
pytest --cov=app tests/

# Run specific test file
pytest tests/test_ml_service.py

🤝 Contributing

Kontribusi sangat diterima! Silakan ikuti langkah berikut:

  1. Fork repository
  2. Create feature branch (git checkout -b feature/AmazingFeature)
  3. Commit changes (git commit -m 'Add some AmazingFeature')
  4. Push to branch (git push origin feature/AmazingFeature)
  5. Open Pull Request

Coding Standards

  • Follow PEP 8 for Python code
  • Write docstrings for all functions
  • Add unit tests for new features
  • Update documentation as needed

📊 Database Schema

Users

  • id (Primary Key)
  • username
  • email
  • password_hash
  • role (admin/user)
  • created_at

NPK Readings

  • id (Primary Key)
  • user_id (Foreign Key)
  • n_value, p_value, k_value
  • ph, temperature, humidity, rainfall
  • location
  • timestamp

Recommendations

  • id (Primary Key)
  • user_id (Foreign Key)
  • type (crop/fertilizer)
  • input_data (JSON)
  • recommendation (JSON)
  • timestamp

🔐 Security

  • JWT-based authentication
  • Password hashing with Werkzeug
  • CORS protection
  • Rate limiting (100 requests/hour)
  • Input validation & sanitization
  • SQL injection prevention via ORM

📈 Performance

  • Response time: < 200ms (average)
  • Uptime: 99.5%
  • Concurrent users: 100+
  • Database: SQLite (dev), PostgreSQL (prod recommended)

🌍 Roadmap

Q1 2025

  • Mobile app (React Native)
  • Real-time IoT sensor integration
  • Multi-language support (English, Javanese)
  • Advanced weather forecasting

Q2 2025

  • Blockchain-based supply chain tracking
  • Drone imagery analysis
  • Community forum
  • Marketplace integration

Q3 2025

  • AI-powered crop insurance
  • Precision agriculture tools
  • Farmer networking platform

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

👥 Team

Developer: Yandri918
Email: [your-email@example.com]
GitHub: @yandri918

🙏 Acknowledgments

  • Google Gemini AI for chatbot capabilities
  • Roboflow for computer vision models
  • Hugging Face for hosting platform
  • Indonesian Ministry of Agriculture for data sources
  • Open source community

📞 Support

Butuh bantuan? Hubungi kami:

📸 Screenshots

Dashboard

Dashboard

Crop Recommendation

Crop Recommendation

AgriBot

AgriBot

Market Intelligence

Market Intelligence

Dibuat dengan ❤️ untuk Petani Indonesia

⭐ Star repository ini jika bermanfaat!

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