Sistem Personalized Recommendation dengan Pendekatan Ontologi untuk Menangani Masalah Obesitas - Yuda, Putu Danny Satria Ananta; Eka Karyawati, Anak Agung Istri Ngurah; Supriana, I Wayan; Astawa, I Gede Santi (JELIKU (Jurnal Elektronik Ilmu Komputer Udayana), 2024)
This study develops a personalized recommendation system using an ontology-based approach to address obesity issues. The system is designed to provide food recommendations tailored to the user's characteristics, such as age, gender, and food preferences. The ontology used enables the system to understand the complex relationships between various types of food and nutrition, thus providing more accurate and relevant recommendations. The system evaluation was conducted using the Technology Acceptance Model (TAM) method, which shows that users find this system useful and easy to use. Survey results indicate that the average Perceived Usefulness (PU) score is 4.167, Perceived Ease of Use (PEOU) is 4.233, Attitude Toward Using (ATU) is 4.033, and Behavioral Intention to Use (BI) is 4.089, indicating that the system is well accepted by users. The study's conclusion shows that the ontology-based recommendation system has good consistency and can enhance user satisfaction in managing their dietary patterns. Suggestions for further development include expanding data collection, improving recommendation algorithms with machine learning techniques, designing a more intuitive interface, and involving users in the system development process. Keywords: Recommendation System, Ontology, Obesity, Information Technology, TAM Evaluation