Personalized Nutrition Recommender System for Hypercholesterolemia Patients Using Ontology and SWRL Approaches - Dalam bentuk buku karya ilmiah

ALYA NABILA MULIANI

Informasi Dasar

48 kali
25.04.535
000
Karya Ilmiah - Skripsi (S1) - Reference

Hypercholesterolemia is a condition characterized by elevated levels of low-density lipoprotein (LDL) cholesterol in the blood, increasing the risk of cardiovascular diseases such as coronary heart disease and stroke. Effective management requires a personalized diet that considers individual preferences, dietary restrictions, and medical needs. While previous studies have utilized ontologies and Semantic Web Rule Language (SWRL) in nutrition recommender systems, few have specifically addressed hypercholesterolemia. To fill this gap, this study presents a personalized nutrition recommender system leveraging ontology and SWRL to provide tailored dietary recommendations for hypercholesterolemia patients. The system integrates with a Telegram chat-bot to offer user-friendly interaction and accessibility. By analyzing patient-specific data, including demographic profiles, health conditions, and dietary preferences, the system generates recommendations to improve cholesterol management. Performance evaluation u

Subjek

RECOMMENDER SYSTEMS
 

Katalog

Personalized Nutrition Recommender System for Hypercholesterolemia Patients Using Ontology and SWRL Approaches - Dalam bentuk buku karya ilmiah
 
iv, 15p.: il,; pdf file
English

Sirkulasi

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Pengarang

ALYA NABILA MULIANI
Perorangan
Z. K. Abdurahman Baizal
 

Penerbit

Universitas Telkom, S1 Informatika
Bandung
2025

Koleksi

Kompetensi

  • CII4H3 - SISTEM PEMBERI REKOMENDASI
  • CII4E4 - TUGAS AKHIR

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