Repository Universitas PakuanHEALTHY FOOD RECOMMENDATION USING THE KNOWLEDGEBASED FILTERING METHOD BASED ON BODY MASS INDEX IN A MOBILE APPLICATIONSatrioPinanditoauthorHEALTHY FOOD RECOMMENDATION USING THE KNOWLEDGEBASED FILTERING METHOD BASED ON BODY MASS INDEX IN A MOBILE APPLICATION Satrio Pinandito1 , Lita Karlitasari2 , Adriana Sari Aryani3 1,2,3Department of Computer Science, Faculty of Mathematics and Natural Science, Pakuan University, Bogor, West Java, 16143, Indonesia Abstract A dietary pattern that aligns with the body’s needs plays an important role in maintaining health and preventing various nutritional problems. However, many people still experience difficulties in determining appropriate types of food based on their individual body conditions. This study aims to design and develop a mobile application that provides healthy food recommendations based on Body Mass Index (BMI) values by applying the Knowledge-Based Filtering method. The application is developed by utilizing calculations of BMI, Basal Metabolic Rate (BMR), and Total Daily Energy Expenditure (TDEE) as the basis for determining users’ daily caloric requirements. Food recommendations are generated based on a rule base constructed from relevant scientific references and validated by nutrition experts. The system is built on the Android platform using the Kotlin programming language and is integrated with the Gemini API service to support the provision of food data and nutritional information. The testing results show that the application is able to provide food recommendations that match users’ needs and operates well across various Android devices. Validation conducted by nutrition experts indicates an improvement in the system’s feasibility level, confirming that the application is suitable for use as a supporting tool in determining healthy food recommendations. Therefore, the developed application is expected to assist users in implementing a more structured, healthy, and sustainable dietary pattern. Keywords: Body Mass Index, Knowledge Based Filtering, Food Recommendation, Mobile Application, AndroidIlmu Komputer2026-02-13Universitas Pakuan;Fakultas Matematika dan Pengetahuan AlamThesis

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