Ontology-Based Low Glycemic Index Menu Recommender System for Patients With Diabetes - Dalam bentuk pengganti sidang - Artikel Jurnal
ATHALIA MALIKA NAJAH
Informasi Umum
Kode
25.04.418
Klasifikasi
000 - General Works
Jenis
Karya Ilmiah - Skripsi (S1) - Reference
Subjek
Recommender Systems
Dilihat
110 kali
Informasi Lainnya
Abstraksi
<strong>Diabetes is a growing chronic health issue driven by lifestyle changes, urbanization, and poor dietary habits. Managing diabetes requires not only medical intervention but also significant lifestyle adjustments, particularly through a healthy and balanced diet. However, existing menu recom-mender systems often fail to consider the importance of a low glycemic index (GI) in meal planning, and they typically lack detailed information such as ingredients, recipes, and nutritional facts. This study seeks to address these short- comings by developing an ontology-based menu recommender system using the Ontology Web Language (OWL) to improve dietary adherence and reduce complications associated with diabetes through personalized low glycemic index menu recommendations. By modeling food data with OWL, the system organizes information about food items, glycemic index values, and nutritional properties to generate personalized recommendations. Evaluation metrics showed a precision of 0.767, recall of 1.0, accur
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Koleksi & Sirkulasi
Tersedia 1 dari total 1 Koleksi
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Pengarang
| Nama | ATHALIA MALIKA NAJAH |
| 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 |
