🗺️ Streamlit_App_GIS_Clustering_FCM_PSO

This is a Streamlit-based web application for performing geospatial clustering using Fuzzy C-Means (FCM) optimized with Particle Swarm Optimization (PSO). In addition to spatial clustering, the app includes a basic blog dashboard to post, view, and manage news or articles related to your data insights.

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🚀 Features

🧠 GIS Clustering Module

• Reads .shp shapefile and Excel datasets containing geographic and indicator data.
• Visualizes clustering results with interactive Plotly Choropleth Mapbox.
• Implements Fuzzy C-Means (FCM) clustering, enhanced with PSO optimization.
• Evaluation metrics: Davies-Bouldin Score and Silhouette Score.

📰 Blog & News Management

• Create, view, and delete posts in a simple blog system.
• Uses SQLite as the backend database.
• Blog cards styled with HTML templates for a clean layout.

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🧱 Folder Structure

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├── app.py                # Main Streamlit app
├── pso_clustering.py     # FCM-PSO clustering logic
├── particle.py           # PSO particle behavior
├── db_functions.py       # Blog-related SQLite functions
├── data.db               # SQLite database
├── dataset/              # Folder for uploaded Excel files
├── gadm36_IDN_2.shp      # Shapefile for Indonesia's regions
├── requirements.txt      # Python dependencies
└── README.md             # Project documentation

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📦 Installation

1. Clone the repository

git clone https://github.com/your-username/Streamlit_App_GIS_Clustering_FCM_PSO.git
cd Streamlit_App_GIS_Clustering_FCM_PSO

2. Create a virtual environment (optional but recommended)

python -m venv venv
source venv/bin/activate     # On Windows: venv\Scripts\activate

3. Install dependencies

pip install -r requirements.txt

4. Run the app

streamlit run app.py

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📊 Screenshots

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📌 Requirements

• Python 3.8+
• Internet connection (for loading Mapbox tiles)
• Shapefile and structured Excel dataset

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📬 Contact

Built with ❤️ by Alexander Tiopan
📧 Email: alexandertiopan1212@gmail.com
💼 LinkedIn: linkedin.com/in/alexander-tiopan-85215117b

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📝 License

This project is licensed under the MIT License.