Pengembangan Sistem Rekomendasi Pembelajaran Personal Berbasis Machine Learning Untuk Mendukung Adaptive Learning

Sri Rahayu Nur Kusumadewi; Ahmad Jodi Cahya

Authors

Sri Rahayu Nur Kusumadewi Universitas Islam Negeri Alauddin Makassar Author
Ahmad Jodi Cahya Universitas Islam Negeri Alauddin Makassar Author

Keywords:

Adaptive Learning, Machine Learning, Sistem Rekomendasi, Pembelajaran Personal, Hybrid Recommender System

Abstract

Perbedaan karakteristik, kemampuan, dan pola aktivitas belajar peserta didik menuntut penerapan pembelajaran yang lebih personal dan adaptif. Penelitian ini bertujuan mengembangkan sistem rekomendasi pembelajaran personal berbasis machine learning untuk mendukung adaptive learning melalui pemanfaatan profil dan aktivitas peserta didik. Sistem dikembangkan melalui tahapan prapemrosesan data, feature engineering, pemodelan machine learning, serta integrasi content-based filtering dan collaborative filtering dalam pendekatan hybrid. Kinerja model dibandingkan menggunakan accuracy, precision, recall, dan F1-score. Hasil pengujian menunjukkan bahwa model hybrid memberikan kinerja terbaik dengan accuracy sebesar 0,91, precision 0,90, recall 0,89, dan F1-score 0,895, lebih tinggi dibandingkan K-Nearest Neighbors, Random Forest, dan Support Vector Machine. Proses pelatihan selama 30 epoch juga menunjukkan pola akurasi training dan validasi yang relatif konsisten tanpa indikasi overfitting yang signifikan. Hasil tersebut menunjukkan bahwa penggabungan informasi berbasis karakteristik materi dan pola interaksi peserta didik berpotensi mendukung rekomendasi pembelajaran yang lebih personal dan adaptif.

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