<mods:mods version="3.3" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-3.xsd" xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><mods:titleInfo><mods:title>HEALTHY FOOD RECOMMENDATION USING THE KNOWLEDGEBASED FILTERING METHOD BASED ON BODY MASS INDEX IN&#13;
A MOBILE APPLICATION</mods:title></mods:titleInfo><mods:name type="personal"><mods:namePart type="given">Satrio</mods:namePart><mods:namePart type="family">Pinandito</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:abstract>HEALTHY FOOD RECOMMENDATION USING THE KNOWLEDGEBASED FILTERING METHOD BASED ON BODY MASS INDEX IN&#13;
A MOBILE APPLICATION&#13;
Satrio Pinandito1&#13;
, Lita Karlitasari2&#13;
, Adriana Sari Aryani3&#13;
1,2,3Department of Computer Science, Faculty of Mathematics and Natural Science, Pakuan University, Bogor,&#13;
West Java, 16143, Indonesia&#13;
Abstract&#13;
A dietary pattern that aligns with the body’s needs plays an important role in maintaining health and preventing various&#13;
nutritional problems. However, many people still experience difficulties in determining appropriate types of food based on&#13;
their individual body conditions. This study aims to design and develop a mobile application that provides healthy food&#13;
recommendations based on Body Mass Index (BMI) values by applying the Knowledge-Based Filtering method. The&#13;
application is developed by utilizing calculations of BMI, Basal Metabolic Rate (BMR), and Total Daily Energy Expenditure&#13;
(TDEE) as the basis for determining users’ daily caloric requirements. Food recommendations are generated based on a rule&#13;
base constructed from relevant scientific references and validated by nutrition experts. The system is built on the Android&#13;
platform using the Kotlin programming language and is integrated with the Gemini API service to support the provision of&#13;
food data and nutritional information. The testing results show that the application is able to provide food recommendations&#13;
that match users’ needs and operates well across various Android devices. Validation conducted by nutrition experts indicates&#13;
an improvement in the system’s feasibility level, confirming that the application is suitable for use as a supporting tool in&#13;
determining healthy food recommendations. Therefore, the developed application is expected to assist users in implementing&#13;
a more structured, healthy, and sustainable dietary pattern.&#13;
Keywords: Body Mass Index, Knowledge Based Filtering, Food Recommendation, Mobile Application, Android</mods:abstract><mods:classification authority="lcc">Ilmu Komputer</mods:classification><mods:originInfo><mods:dateIssued encoding="iso8061">2026-02-13</mods:dateIssued></mods:originInfo><mods:originInfo><mods:publisher>Universitas Pakuan;Fakultas Matematika dan Pengetahuan Alam</mods:publisher></mods:originInfo><mods:genre>Thesis</mods:genre></mods:mods>