Jalur Obat

AI-Based Counterfeit Medicine Distribution Detection System

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1. Project Overview

Jalur Obat is an AI-based application designed to monitor and analyze medicine distribution journeys in order to detect counterfeit risks. The system combines:

• A web application
• A Node.js backend
• A PostgreSQL database
• A Python-based AI service

The application records medicine journey data, evaluates risk using AI scoring, and classifies the overall safety status of distributed medicines.

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2. System Requirements

Before running the project, ensure the following tools are installed:

• Visual Studio Code
• Git
• Node.js (npm included)
• Python (with venv support)
• PostgreSQL
• pgAdmin 4

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3. Project Setup

3.1 Clone the Repository

1. Open a terminal.

2. Navigate to the directory where you want to store the project:

   cd Documents

3. Clone the repository:

   git clone https://github.com/DlegendZ/Jalur-Obat.git

4. Enter the project directory:

   cd jalur-obat

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3.2 Install Node.js Dependencies

1. Open a terminal inside the project directory.

2. Install required dependencies:

   npm install express pg dotenv cors

3. Confirm that the node_modules folder is created.

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3.3 Backend Python Environment (AI Service)

1. Navigate to the backend folder:

   cd backend

2. Create a virtual environment:

   python -m venv venv

3. Activate the virtual environment:

   venv\Scripts\activate

4. Install required Python packages:

   pip install -r requirement.txt

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4. Database Configuration

4.1 Create the Database

1. Open pgAdmin 4.
2. Create a new database (example name: medicine_journey).

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4.2 Create Tables

Execute the following DDL script inside the newly created database:

CREATE TABLE medicine_info (
    report_id SERIAL PRIMARY KEY,
    serial_number TEXT NOT NULL,
    medicine_name TEXT NOT NULL,
    current_location TEXT NOT NULL,
    quantity INTEGER NOT NULL,
    additional TEXT,
    temperature NUMERIC(5,2) NOT NULL,
    humidity NUMERIC(5,2) NOT NULL,
    ai_score_fake_result NUMERIC(5,2),
    ai_journey_score TEXT NOT NULL CHECK (
        ai_journey_score IN ('Safe', 'Need Attention', 'Full Attention', 'Faked', 'Unknown')
    ),
    overall_status TEXT NOT NULL CHECK (
        overall_status IN ('Safe', 'Need Attention', 'Bad')
    ),
    expedition_type TEXT NOT NULL CHECK (
        expedition_type IN ('Land', 'Air', 'Sea')
    ),
    created_at TIMESTAMP DEFAULT NOW(),
    officer_id TEXT NOT NULL,
    journey_status TEXT NOT NULL CHECK (
        journey_status IN ('start', 'update', 'end')
    )
);

Grant privileges (replace YOUR_USERNAME with your PostgreSQL username):

GRANT ALL PRIVILEGES ON TABLE medicine_info TO YOUR_USERNAME;
GRANT USAGE, SELECT ON SEQUENCE medicine_info_report_id_seq TO YOUR_USERNAME;

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4.3 Environment Variables

Update the .env file with your PostgreSQL credentials:

DB_USER=your_pgadmin_username
DB_PASSWORD=your_pgadmin_password
DB_NAME=medicine_journey
DB_HOST=localhost
DB_PORT=5432

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5. Running the System

5.1 Start the Web Application

1. Open a terminal in the directory containing package.json.

2. Run:

   npm run dev

3. Open the application in a browser:

   http://localhost:3000
   

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5.2 Start the AI Service

1. Open Visual Studio Code.

2. Open the jalur-obat project.

3. Open the terminal and navigate to the backend folder:

   cd backend

4. Activate the virtual environment:

   venv\Scripts\activate

5. Start the AI server:

   uvicorn app.main:app --reload

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5.3 Start the Database Server

1. Navigate to the app folder (contains server.js).

2. Open a system terminal (CMD).

3. Run:

   node server.js

4. The backend is now connected to the database.

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6. System Workflow Summary

• Frontend collects medicine journey data.
• Node.js backend stores and retrieves data from PostgreSQL.
• AI service evaluates risk and generates AI scores.
• Database stores all journey records and evaluation results.

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7. Conclusion

Jalur Obat provides an integrated solution for tracking medicine distribution and detecting counterfeit risks through structured data collection and AI-based evaluation. Proper setup of dependencies, database configuration, and service execution is required to run the system successfully.