Mesin Rekomendasi Menggunakan Algoritma Alternating Least Square (ALS) pada Goodreads
DOI:
https://doi.org/10.24014/coreit.v6i2.11578Abstract
Sistem rekomendasi merupakan sistem yang dapat memberikan rekomendasi berupa prediksi rating pada suatu item. Ada banyak cara dalam merekomendasikan suatu item kepada pengguna, salah satunya adalah Alternating Least Square. Goodreads adalah situs web buku yang menjelaskan sinopsis dan memberi peringkat untuk buku, dan Goodreads membagikan peringkat pengguna mereka ke item di Kaggle untuk dianalisis. Oleh karena itu, penulis ingin merancang, mengimplementasikan, menguji serta ingin mengevaluasi mesin rekomendasi buku Goodreads mulai dari rating pengguna hingga item sebagai alternatif pemecahan masalah dari rekomendasi peringkat buku di Goodreads sekarang ini. Terdapat 981.756 data yang diolah menggunakan Alternating Least Square dengan 80% data latih dan 20% data uji. Hasil prediksi dievaluasi dengan Mean Absolute Error (MAE) dan Root Mean Square Error (RMSE). Hasil penelitian ini menunjukkan bahwa Root Mean Square Error 0.67 dan Mean Absolute Error 0.52 dan dapat dikatakan mesin yang dibuat memiliki error varians yang kecil karena memiliki kesalahan di bawah 1.00.
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