Documentation BukuKu

🔧 Instalasi & Menjalankan

Install dependensi:

pip install flask flask-cors mysql-connector-python python-dotenv google.generativeai

Buat file .env dan isi dengan konfigurasi database:

MYSQL_HOST=localhost
MYSQL_USER=root
MYSQL_PASSWORD= 
MYSQL_PORT=3308

BOOK_SERVICE_PORT=5000
LOAN_SERVICE_PORT=5001
USER_SERVICE_PORT=5002
PREDICT_SERVICE_PORT=5003

MYSQL_DB_BOOK=book_management_uts_db 
MYSQL_DB_LOAN=loan_management_uts_db 
MYSQL_DB_USER=user_management_uts_db

URL=http://localhost

GEMINI_API_KEY=YOUR_GEMINI_KEY

Sesuaikan juga konfigurasi pada file js/config.js

window.env = {
  URL: "http://localhost",
  BOOK_SERVICE_PORT: 5000,
  LOAN_SERVICE_PORT: 5001,
  USER_SERVICE_PORT: 5002,
  PREDICT_SERVICE_PORT: 5003,
};

Import file database_setup.sql ke database
Jalankan service (masing-masing beda terminal):

python -m http.server 8000
py book_service.py
py user_service.py
py loan_service.py
py predict_service.py

API Documentation

📖 BookService API Documentation

BookService adalah bagian dari sistem manajemen perpustakaan yang menangani operasi terkait buku. API ini dibangun menggunakan Flask dan terhubung dengan MySQL.

Default port: 5000

📂 Daftar Endpoint

`GET /books`

Ambil semua data buku.

Response 200:

[
  {
    "id": 1,
    "title": "Example Book",
    "author": "John Doe",
    "isbn": "1234567890",
    "total_copies": 5,
    "available_copies": 2,
    "cover_url": "http://example.com/cover.jpg"
  },
  {
    "id": 2,
    "title": "Example Book 2",
    "author": "Mary Jane",
    "isbn": "3344556677",
    "total_copies": 5,
    "available_copies": 2,
    "cover_url": "http://example.com/cover.jpg"
  },
]

Response 500: { "error": "Error message" }

`GET /books/<book_id>`

Ambil data buku berdasarkan ID.

Response 200:

{
  "id": 1,
  "title": "Example Book",
  "author": "John Doe",
  "isbn": "1234567890",
  "total_copies": 5,
  "available_copies": 2,
  "cover_url": "http://example.com/cover.jpg"
}

Response 404: { "error": "Book not found" }
Response 500: { "error": "Error message" }

`POST /books`

Tambah buku baru.

Request Body JSON:

{
  "title": "New Book",
  "author": "Jane Smith",
  "isbn": "1122334455",
  "total_copies": 4,
  "available_copies": 4,
  "cover_url": "http://example.com/cover.jpg"
}

Response 201: { "message": "Book created successfully", "book_id": 1 }
Response 500: { "error": "Error message" }

`PUT /books/<book_id>`

Update data lengkap buku berdasarkan ID.

Request Body JSON:

{
  "title": "Updated Book",
  "author": "Jane Smith",
  "isbn": "1122334455",
  "total_copies": 4,
  "available_copies": 3,
  "cover_url": "http://example.com/cover.jpg"
}

Response 200: { "message": "Book updated successfully" }
Response 404: { "error": "Book not found" }
Response 500: { "error": "Error message" }

`PUT /books/<book_id>/availability`

Update jumlah available_copies buku secara dinamis (tambah/kurang 1).

Request Body JSON:

{
  "increment": true
}

increment: true → tambah 1
increment: false → kurangi 1
Response 200:

{
  "message": "Book availability updated",
  "available_copies": 3
}

Response 400: Validasi stok (misalnya habis atau sudah penuh)
Response 404: { "error": "Book not found" }
Response 500: { "error": "Error message" }

`DELETE /books/<book_id>`

Hapus buku berdasarkan ID.

Response 200: { "message": "Book deleted successfully" }
Response 404: { "error": "Book not found" }
Response 500: { "error": "Error message" }

`GET /books/search?q=keyword`

Cari buku berdasarkan title atau author.

Query Param: q (kata kunci pencarian)
Response 200: Array hasil pencarian
Response 400: { "error": "Query parameter 'q' is required" }
Response 500: { "error": "Error message" }

📖 UserService API Documentation

UserService adalah bagian dari sistem manajemen perpustakaan yang menangani data pengguna dan integrasi dengan LoanService untuk menampilkan histori peminjaman.

Default port: 5002

📂 Daftar Endpoint

`GET /users`

Ambil semua user.

Response 200:

[
  {
    "id": 1,
    "name": "John Doe",
    "email": "john@example.com",
    "loan_history": 2
  },
  {
    "id": 1,
    "name": "Mary Jane",
    "email": "jane@example.com",
    "loan_history": 3
  }
]

Response 500: { "error": "Error message" }

`GET /users/<user_id>`

Ambil data user berdasarkan ID beserta jumlah pinjaman.

Response 200:

{
  "id": 1,
  "name": "John Doe",
  "email": "john@example.com",
  "loan_history": 2
}

Response 404: { "error": "User not found" }
Response 500: { "error": "Error message" }

`POST /users`

Tambahkan user baru.

Request Body JSON:

{
  "name": "John Doe",
  "email": "john@example.com"
}

Response 201: { "message": "User created successfully", "user_id": 1 }
Response 500: { "error": "Error message" }

`PUT /users/<user_id>`

Update user berdasarkan ID.

Request Body JSON:

{
  "name": "Jane Doe",
  "email": "jane@example.com"
}

Response 200: { "message": "User updated successfully" }
Response 404: { "error": "User not found" }
Response 500: { "error": "Error message" }

`DELETE /users/<user_id>`

Hapus user berdasarkan ID.

Response 200: { "message": "User deleted successfully" }
Response 404: { "error": "User not found" }
Response 500: { "error": "Error message" }

📖 LoanService API Documentation

LoanService adalah bagian dari sistem manajemen perpustakaan yang menangani data peminjaman buku dan berinteraksi dengan BookService untuk memperbarui ketersediaan buku.

Default port: 5001

📂 Daftar Endpoint

`GET /loans`

Ambil semua data peminjaman buku.

Response 200:

[
  {
    "id": 1,
    "user_id": 1,
    "book_id": 2,
    "loan_date": "2025-04-18",
    "return_date": "2025-05-01"
  }
]

Response 500: { "error": "Error message" }

`GET /loans/<loan_id>`

Ambil data peminjaman berdasarkan ID pinjaman.

Response 200:

{
  "id": 1,
  "user_id": 1,
  "book_id": 2,
  "loan_date": "2025-04-18",
  "return_date": "2025-05-01"
}

Response 404: { "error": "Loan not found" }
Response 500: { "error": "Error message" }

`POST /loans`

Tambah peminjaman buku.

Request Body JSON:

{
  "user_id": 1,
  "book_id": 2,
  "loan_date": "2025-04-18",
  "return_date": "2025-05-01"
}

Response 201: { "message": "Loan created successfully", "loan_id": 1 }
Response 400: { "error": "Book is not available for loan" }
Response 404: { "error": "Book not found" }
Response 500: { "error": "Error message" }

`PUT /loans/<loan_id>`

Update data peminjaman berdasarkan ID.

Request Body JSON:

{
  "user_id": 1,
  "book_id": 2,
  "loan_date": "2025-04-18",
  "return_date": "2025-05-05"
}

Response 200: { "message": "Loan updated successfully" }
Response 404: { "error": "Loan not found" }
Response 500: { "error": "Error message" }

`DELETE /loans/<loan_id>`

Hapus data peminjaman buku berdasarkan ID.

Response 200: { "message": "Loan deleted successfully" }
Response 404: { "error": "Loan not found" }
Response 500: { "error": "Error message" }

`GET /loans/user/<user_id>`

Ambil semua peminjaman berdasarkan ID user.

Response 200:

[
  {
    "id": 1,
    "user_id": 1,
    "book_id": 2,
    "loan_date": "2025-04-18",
    "return_date": "2025-05-01"
  }
]

Response 500: { "error": "Error message" }

📖 PredictService API Documentation

PredictService adalah bagian dari sistem manajemen perpustakaan yang melakukan prediksi jumlah peminjaman buku menggunakan data historis peminjaman buku.

Default port: 5003

📂 Daftar Endpoint

`GET /predict/<int:model_no>`

Memprediksi jumlah peminjaman untuk bulan tertentu.

Response 200:

    "data": {
        "prediction": 5
    },
    "success": true
}

Response 400: {"success": False, "message": result.get("error", "Unknown error"}
Response 500: {"success": False, "message": str(e)}

`GET /evaluate`

Mendapatkan nilai error untuk masing-masing model, penilaian model menggunakan MAE, MSE, R² SCORE, dan RMSE.

Response 200:

    {
    "data": {
        "model_1": {
            "mae": 0.45746131719608274,
            "mse": 0.68751443399021,
            "r2_score": 0.8721626584230917,
            "rmse": 0.829164901566757
        },
        "model_2": {
            "mae": 0.48320135411098675,
            "mse": 0.6700247413457315,
            "r2_score": 0.8752316807557716,
            "rmse": 0.8185503902300283
        },
        "model_3": {
            "mae": 0.4313456130538823,
            "mse": 0.5411683946130689,
            "r2_score": 0.906165398061277,
            "rmse": 0.7356414851087919
        },
        "model_4": {
            "mae": 0.8216825988766604,
            "mse": 1.4909382708322145,
            "r2_score": 0.6751121619003155,
            "rmse": 1.2210398317959223
        }
    },
    "success": true
}

Response 500: {"success": False, "message": str(e)}

`GET /loans-total-data`

Merupakan route yang berkomunikasi langsung sebagai consumer dengan LoanService untuk mengakses data jumlah peminjaman dari bulan Januari 2022 hingga Maret 2025

Response 200:

{
    "data": [
        {
            "book_id": 1,
            "borrowed_count": 5,
            "date": "Mon, 31 Jan 2022 00:00:00 GMT",
            "is_low_season": 0,
            "is_peak_season": 0
        },
        {
            "book_id": 1,
            "borrowed_count": 8,
            "date": "Mon, 28 Feb 2022 00:00:00 GMT",
            "is_low_season": 0,
            "is_peak_season": 1
        },
        ... (seluruh data sampai "book_id = 6")
    ],
    "success": true
}

Response 500: {"success": False, "message": str(e)}

`GET /predict_all`

Prediksi jumlah peminjaman pada bulan berikutnya menggunakan model ML

Response 200:

{
    "data": {
        "predictions": {
            "model_1": {
                "low_only": 5,
                "no_season": 5,
                "peak_only": 5
            },
            "model_2": {
                "low_only": 5,
                "no_season": 5,
                "peak_only": 5
            },
            "model_3": {
                "low_only": 8,
                "no_season": 8,
                "peak_only": 8
            },
            "model_4": {
                "low_only": 10,
                "no_season": 10,
                "peak_only": 10
            }
        },
        "target_date": "2025-04-30"
    },
    "success": true
}

Response 500: {"success": False, "message": str(e)}

`POST /predict_analyze`

Mendapatkan hasil analisis AI terkait hasil prediksi ML

Response 200:

{
    "data": {
        "analysis": "Data prediksi peminjaman buku pada 30 April 2025 menunjukkan variasi hasil antar model.  Model 3 dan Model 2 memiliki error terendah (MSE dan RMSE terkecil, R-squared tertinggi), menunjukkan akurasi prediksi yang lebih baik dibandingkan model lainnya.  Meskipun Model 4 memprediksi jumlah peminjaman tertinggi (10 untuk semua skenario), metrik error-nya jauh lebih tinggi, mengindikasikan prediksi yang kurang akurat.  Semua model memprediksi jumlah peminjaman yang serupa antar skenario (\"peak_only\", \"low_only\", \"no_season\"), menyiratkan bahwa model-model ini mungkin belum cukup menangkap pengaruh musiman atau faktor lain yang memengaruhi peminjaman buku.  Secara keseluruhan, Model 3 tampak sebagai model terbaik berdasarkan metrik error yang diberikan, walaupun diperlukan analisis lebih lanjut untuk memastikan keandalan prediksinya.\n",
        "error_metrics": {
            "model_1": {
                "mae": 0.45746131719608274,
                "mse": 0.68751443399021,
                "r2_score": 0.8721626584230917,
                "rmse": 0.829164901566757
            },
            "model_2": {
                "mae": 0.48320135411098675,
                "mse": 0.6700247413457315,
                "r2_score": 0.8752316807557716,
                "rmse": 0.8185503902300283
            },
            "model_3": {
                "mae": 0.4313456130538823,
                "mse": 0.5411683946130689,
                "r2_score": 0.906165398061277,
                "rmse": 0.7356414851087919
            },
            "model_4": {
                "mae": 0.8216825988766604,
                "mse": 1.4909382708322145,
                "r2_score": 0.6751121619003155,
                "rmse": 1.2210398317959223
            }
        },
        "predictions": {
            "predictions": {
                "model_1": {
                    "low_only": 5,
                    "no_season": 5,
                    "peak_only": 5
                },
                "model_2": {
                    "low_only": 5,
                    "no_season": 5,
                    "peak_only": 5
                },
                "model_3": {
                    "low_only": 8,
                    "no_season": 8,
                    "peak_only": 8
                },
                "model_4": {
                    "low_only": 10,
                    "no_season": 10,
                    "peak_only": 10
                }
            },
            "target_date": "2025-04-30"
        }
    },
    "success": true
}

Response 500: {"success": False, "message": str(e)}

Name		Name	Last commit message	Last commit date
Latest commit History 9 Commits
css		css
js		js
prediction_service		prediction_service
.gitignore		.gitignore
README.md		README.md
book_service.py		book_service.py
config.py		config.py
database_setup.sql		database_setup.sql
docker-compose.yml		docker-compose.yml
dockerfile.book_service		dockerfile.book_service
dockerfile.frontend		dockerfile.frontend
dockerfile.loan_service		dockerfile.loan_service
dockerfile.predict_service		dockerfile.predict_service
dockerfile.user_service		dockerfile.user_service
index.html		index.html
loan_service.py		loan_service.py
predict_service.py		predict_service.py
requirements.txt		requirements.txt
user_service.py		user_service.py

salikarth/EAI2025

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Documentation BukuKu

🔧 Instalasi & Menjalankan

API Documentation

📖 BookService API Documentation

📂 Daftar Endpoint

GET /books

GET /books/<book_id>

POST /books

PUT /books/<book_id>

PUT /books/<book_id>/availability

DELETE /books/<book_id>

GET /books/search?q=keyword

📖 UserService API Documentation

📂 Daftar Endpoint

GET /users

GET /users/<user_id>

POST /users

PUT /users/<user_id>

DELETE /users/<user_id>

📖 LoanService API Documentation

📂 Daftar Endpoint

GET /loans

GET /loans/<loan_id>

POST /loans

PUT /loans/<loan_id>

DELETE /loans/<loan_id>

GET /loans/user/<user_id>

📖 PredictService API Documentation

📂 Daftar Endpoint

GET /predict/<int:model_no>

GET /evaluate

GET /loans-total-data

GET /predict_all

POST /predict_analyze

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`GET /books`

`GET /books/<book_id>`

`POST /books`

`PUT /books/<book_id>`

`PUT /books/<book_id>/availability`

`DELETE /books/<book_id>`

`GET /books/search?q=keyword`

`GET /users`

`GET /users/<user_id>`

`POST /users`

`PUT /users/<user_id>`

`DELETE /users/<user_id>`

`GET /loans`

`GET /loans/<loan_id>`

`POST /loans`

`PUT /loans/<loan_id>`

`DELETE /loans/<loan_id>`

`GET /loans/user/<user_id>`

`GET /predict/<int:model_no>`

`GET /evaluate`

`GET /loans-total-data`

`GET /predict_all`

`POST /predict_analyze`

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