Authors: Hidayat H, Muhammad Salman Al-Farisi
Abstract
Obesity has become a significant global health issue, affecting populations in both developed and developing countries. The World Health Organization (WHO) reported a substantial rise in obesity rates since 1990, with 43% of individuals classified as overweight in 2022. This study aimed to design and implement an Android-based diet and jogging recommendation application targeting adults. Following the Waterfall model, the research adhered to a structured, sequential process that included requirements analysis, system design, implementation, testing, deployment, and maintenance phases. The application calculates Body Mass Index (BMI) based on user input, such as weight, height, age, and gender, categorizing individuals into seven classifications: Underweight, Normal weight, Pre-obesity, Obesity class I, II, and III. Personalized diet and exercise recommendations are then provided to help users achieve and sustain a healthy weight. The app integrates the Google Maps API to track jogging routes and the Low Carb Recipes API to offer calorie-based meal suggestions. Additionally, the Jogging Tracking feature allows users to monitor their jogging history. The results demonstrate that the application effectively delivers customized dietary and physical activity recommendations, aiding users in managing their caloric intake and maintaining consistent exercise routines. The system proves to be both functional and practical, offering a valuable tool in the fight against obesity, particularly in Indonesia. This research contributes to addressing the global obesity crisis by providing an accessible, technology-driven solution. © School of Engineering, Taylor’s University.
Author keywords
Android; BMI; Calorie; Jogging; Obesity
This article can be accessed at https://www.scopus.com/pages/publications/85214310304

