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primary topic: HEALTHY FOOD RECOMMENDATION USING THE KNOWLEDGEBASED FILTERING METHOD BASED ON BODY MASS INDEX IN A MOBILE APPLICATION

HEALTHY FOOD RECOMMENDATION USING THE KNOWLEDGEBASED FILTERING METHOD BASED ON BODY MASS INDEX IN A MOBILE APPLICATION
type: Thesis
type: Article
abstract: HEALTHY 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, Android
date: 2026-02-13
status: published
author list: authors
type: EPrint
type: ThesisEPrint
is part of: repository
subject: Ilmu Komputer

Universitas Pakuan
type: Organization

Fakultas Matematika dan Pengetahuan Alam, Universitas Pakuan
type: Organization

Lita Karlitasari
type: Person
given name: Lita
family name: Karlitasari

Satrio Pinandito
type: Person
given name: Satrio
family name: Pinandito

Adriana Sari Aryani
type: Person
given name: Adriana
family name: Sari Aryani

Fakultas Matematika dan Ilmu Pnegetahuan Alam
type: Organization

Program Studi Ilmu Komputer
type: Organization

HTML Summary of #10747 HEALTHY FOOD RECOMMENDATION USING THE KNOWLEDGEBASED FILTERING METHOD BASED ON BODY MASS INDEX IN A MOBILE APPLICATION
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primary topic: HEALTHY FOOD RECOMMENDATION USING THE KNOWLEDGEBASED FILTERING METHOD BASED ON BODY MASS INDEX IN A MOBILE APPLICATION

Ilmu Komputer
type: Concept