Evaluation of Diversity and Novelty of Recommendation System on Digital Learning Platform Based on User Usability and Satisfaction - Dalam bentuk pengganti sidang - Artikel Jurnal
ELSAM RAFI SAPUTRA
Informasi Umum
Kode
25.04.1054
Klasifikasi
000 - General Works
Jenis
Karya Ilmiah - Skripsi (S1) - Reference
Subjek
Software Engineering
Dilihat
86 kali
Informasi Lainnya
Abstraksi
Digital learning platforms, such as Duolingo and Udemy, offer a large amount of content, making it difficult for users to find materials that suit their learning needs. Due to this, recommendation systems were implemented to improve user satisfaction. Although traditional systems focus on accuracy, this research highlights the importance of diversity and novelty by offering diverse and novel recommendations that introduce users to unfamiliar or surprising recommendations. Using kmeans clustering, Intra-List Diversity (ILD), and Mean SelfInformation (MSI) metrics, this research evaluates the effectiveness of the system. The results show an ILD of 0.616044328 and an MSI of 0.628135613, which indicates diverse and novel recommendations. User feedback on the user satisfaction questionnaire survey further confirmed satisfaction and usability in highlighting the value of integrating diversity and novelty into the recommendation system on the e-learning platform.
Koleksi & Sirkulasi
Tersedia 1 dari total 1 Koleksi
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Pengarang
| Nama | ELSAM RAFI SAPUTRA |
| Jenis | Perorangan |
| Penyunting | Dana Sulistiyo Kusumo |
| 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 |
