Add README.md with Hugging Face configuration

README.md

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+---
+title: Iris Flower Classification
+emoji: 🌸
+colorFrom: blue
+colorTo: purple
+sdk: docker
+sdk_version: "4.36.2"
+app_file: app.py
+pinned: false
+license: mit
+---
+
+# 🌸 Iris Flower Classification API
+
+Aplikasi Machine Learning untuk klasifikasi bunga Iris menggunakan Decision Tree Algorithm. API ini dapat memprediksi spesies bunga Iris (Setosa, Versicolor, atau Virginica) berdasarkan fitur morfologi bunga.
+
+## 📊 Dataset & Model
+
+- **Dataset**: Iris Dataset dari scikit-learn
+- **Algorithm**: Decision Tree Classifier
+- **Features**: 
+  - Sepal Length (cm)
+  - Sepal Width (cm) 
+  - Petal Length (cm)
+  - Petal Width (cm)
+- **Target Classes**: Setosa, Versicolor, Virginica
+
+## 🚀 API Endpoints
+
+### 1. Home Page
+```
+GET /
+```
+Web interface interaktif untuk testing model
+
+### 2. Predict Species
+```
+POST /predict
+Content-Type: application/json
+
+{
+  "sepal_length": 5.1,
+  "sepal_width": 3.5,
+  "petal_length": 1.4,
+  "petal_width": 0.2
+}
+```
+
+### 3. Model Information
+```
+GET /model-info
+```
+Informasi detail tentang model dan feature importance
+
+### 4. Health Check
+```
+GET /health
+```
+Status kesehatan API
+
+## 🧪 Example Usage
+
+### Prediksi Setosa:
+```json
+{
+  "sepal_length": 5.1,
+  "sepal_width": 3.5,
+  "petal_length": 1.4,
+  "petal_width": 0.2
+}
+```
+
+### Prediksi Versicolor:
+```json
+{
+  "sepal_length": 7.0,
+  "sepal_width": 3.2,
+  "petal_length": 4.7,
+  "petal_width": 1.4
+}
+```
+
+### Prediksi Virginica:
+```json
+{
+  "sepal_length": 6.3,
+  "sepal_width": 3.3,
+  "petal_length": 6.0,
+  "petal_width": 2.5
+}
+```
+
+## 📈 Model Performance
+
+- **Accuracy**: 100% (pada test set)
+- **Algorithm**: Decision Tree dengan random_state=42
+- **Training Data**: 120 samples
+- **Test Data**: 30 samples
+
+## 🔗 Key Decision Rules
+
+Berdasarkan Decision Tree yang dihasilkan:
+
+1. **Setosa**: Petal Length ≤ 2.45 cm
+2. **Versicolor**: Petal Length > 2.45 cm AND Petal Width ≤ 1.75 cm
+3. **Virginica**: Petal Length > 2.45 cm AND Petal Width > 1.75 cm
+
+## 🛠️ Technology Stack
+
+- **Backend**: Flask + Python 3.11
+- **ML**: scikit-learn, pandas, numpy
+- **Model Persistence**: joblib
+- **Container**: Docker
+- **Deployment**: Hugging Face Spaces
+
+## 👨‍💻 Author
+
+Tugas 27 - Machine Learning Model Deployment
+**Universitas/Institusi**: Infinite Learning