Ontology-Based Recommender System for Personalized Physical Exercise in Obesity Management


  • Widi Sayyd Fadhil Muhammad School of computing, Telkom University Bandung, Indonesia
  • Z. K. A Baizal Telkom University
  • Ramanti Dharayani School of computing, Telkom University Bandung, Indonesia




Chatbot, Ontology, Recommender System, SWRL


In Indonesia, obesity is a serious health issue, and rates have risen recently because of sedentary lifestyles and poor eating practices. We suggest a proactive self-care suggestion system specifically created for Indonesians who are dealing with obesity to address this problem. Our recommender system attempts to give customers individualized suggestions for healthy lifestyle modifications that will make it easier for them to manage their weight. Because social media is so widely used in Indonesia, we created our system as a Telegram Chatbot. Our system may provide personalized suggestions based on a particular gender, activity level, fat mass, and difficulty of exercise that are relevant to Indonesians by fusing the user's ontological profile with generic clinical guidelines and standards for the management of obesity. Ontologies with Semantic Web Rule Language (SWRL) were used in the development of our system since SWRL ontologies are thought to perform better. Evaluations carried out using case studies and expert verification illustrate the usefulness of our suggested method, and the validated result of 88.8 percent demonstrates that our system can deliver good suggestion results for the user.


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Author Biographies

Widi Sayyd Fadhil Muhammad, School of computing, Telkom University Bandung, Indonesia



Ramanti Dharayani, School of computing, Telkom University Bandung, Indonesia




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How to Cite

Muhammad, W. S. F. ., Baizal, Z. K. A., & Dharayani, R. . (2023). Ontology-Based Recommender System for Personalized Physical Exercise in Obesity Management. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 7(3), 1699-1708. https://doi.org/10.33395/sinkron.v8i3.12689