Tentang Proyek

UTS Praktikum Kecerdasan Buatan — Prediksi Biaya Asuransi Kesehatan

Informasi Proyek

Mata Kuliah Praktikum Kecerdasan Buatan
Semester 4 (Genap) 2025/2026
Topik Prediksi Biaya Asuransi Kesehatan
Dataset Medical Cost Personal Dataset (Kaggle)
Lisensi Dataset CC0: Public Domain

Tech Stack

🐍 Python 3.12
🌶️ Flask
🤖 TensorFlow / Keras
📊 scikit-learn
🔢 NumPy / Pandas
📈 Chart.js

Alur Metodologi

1
Eksplorasi Data (EDA)

Analisis distribusi, korelasi, outlier, dan statistik deskriptif

2
Preprocessing

Label encoding, StandardScaler, train/val/test split (70:15:15)

3
Pelatihan 5 Model ML

LR, ANN, RNN/LSTM, K-Means, Backpropagation

4
Evaluasi & Komparasi

MAE, RMSE, R², MAPE, Silhouette Score

5
Deploy Aplikasi Web

Flask backend + frontend responsif dengan prediksi real-time

Referensi

  1. Choi, B. G., et al. (2020). Machine learning in medicine. Korean Circulation Journal.
  2. Hochreiter, S. & Schmidhuber, J. (1997). Long short-term memory. Neural Computation.
  3. MacQueen, J. (1967). Some methods for classification. Berkeley Symposium.
  4. Pedregosa, F., et al. (2011). Scikit-learn: Machine learning in Python. JMLR.
  5. Rumelhart, D. E., et al. (1986). Learning representations by back-propagating errors. Nature.
  6. Abadi, M., et al. (2016). TensorFlow: A system for large-scale ML. OSDI.
  7. Lantz, B. (2013). Machine Learning with R. Packt Publishing.
  8. Géron, A. (2019). Hands-On Machine Learning. O'Reilly.