Personalized Korean Drama Series Recommender System Using Singular Value Decomposition - Dalam bentuk buku karya ilmiah
AISHA FARIZKA MAWLA
Informasi Umum
Kode
25.04.520
Klasifikasi
000 - General Works
Jenis
Karya Ilmiah - Skripsi (S1) - Reference
Subjek
Recommender Systems
Dilihat
61 kali
Informasi Lainnya
Abstraksi
Korean drama series recommender systems aim to assist users in finding Korean drama series that match their preferences. Based on previous studies, there are several recommender systems on Korean drama series with various methods, but many of them are still limited to certain criteria, such as users’ favorite actors or genres, thus reducing the variety of recommendations. Therefore, we propose a recommender system for Korean drama series focusing on the MyDramaList dataset using the Singular Value Decomposition (SVD) method that utilizes other users’ ratings, thus enabling more in-depth identification of user preference patterns and items. The SVD method improves recommendation accuracy by extracting impor- tant features and overcoming sparsity issues, resulting in more relevant and personalized recommendations. Based on the test results, the SVD method performed best compared to the baseline K-Means and K-NN methods with an RMSE value of 1.443 and MAE of 0.900, reflecting a high level of prediction accuracy.
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Koleksi & Sirkulasi
Tersedia 1 dari total 1 Koleksi
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Pengarang
| Nama | AISHA FARIZKA MAWLA |
| Jenis | Perorangan |
| Penyunting | Z. K. Abdurahman Baizal |
| Penerjemah |
Penerbit
| Nama | Universitas Telkom, S1 Informatika |
| Kota | Bandung |
| Tahun | 2025 |
Sirkulasi
| Harga sewa | IDR 0,00 |
| Denda harian | IDR 0,00 |
| Jenis | Non-Sirkulasi |
