Food Menu Recommendationsusing Content-based Filtering Method

Food Menu Recommendationsusing Content-based Filtering Method

Content-basedFiltering, Disease constraint, Food recommender, User preferences

A nutritionally imbalanced body poses significant health risks. Achieving nutritional balance and maintaining a healthy diet are therefore essential. One of the major challenges in this regard arises when a user'sdietary preferences conflict with their health conditions. To address this issue, it is necessary to develop a system that not only identifies nutritional needs and assesses their adequacy but also takes into account users’ medical histories. This study aims to develop a food menu recommender system that integrates nutritional requirements, user preferences, and disease history. Content-based filtering was employed to measure the similarity between user profiles and the available dataset. A weighting modelwas incorporated to accommodate food restrictions associated with specific health conditions. The dataset used in this study was obtained from the Center for Nutrition Research and Development and Food, Ministry of Health of the Republic of Indonesia. Theresearch process includes data collection, pre-processing, user profile identification, and the generation of food recommendations. Additionally, this study explores the integration of user preferences and disease recordsusing a binary vectorto improve recommendation accuracy. The findings indicate that the developed system successfully provides food recommendations that are not only calorically adequate and nutritionally balanced, but also consistent with the recommended macronutrient distribution for protein, fat, and carbohydrates.

Abidatul Izzah1, Kunti Eliyen2, Ellya Nurfarida3, Benni A.Nugroho4, Miftakhul Huda5, Mutia T.Alawia

https://ijicom.respati.ac.id/index.php/ijicom/article/view/186/122

nternational Journal of Informatics and Computation (IJICOM)

2025

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English

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