SMART DIET ASSISTANT APPLICATION FEATURING A FOOD DIARY AND MENU RECOMMENDATIONS BASED ON THE DECISION TREE ALGORITHM

Abstract

Body health is strongly influenced by a balanced and regular diet, yet many people still struggle to manage their daily food intake according to their calorie needs and health conditions. This study aims to develop Smart Diet Assistant, an Android-based application that helps users record daily food consumption through a food diary feature and provides healthy menu recommendations using the Decision Tree algorithm. The application was developed using Kotlin with a Jetpack Compose interface, Room Database for local storage, and an MVVM architectural approach.

User data including age, gender, body weight, height, activity level, and medical history are used to calculate daily calorie needs via the Mifflin-St Jeor equation and to determine menu recommendations based on BMI status and health conditions such as diabetes, gastritis, and high cholesterol. The Decision Tree applies a rule-based approach to filter appropriate menus for each user profile.

Testing was conducted through Black Box Testing across two iterations and User Acceptance Testing (UAT) with 27 respondents. All functional scenarios passed in the final iteration. UAT results showed a usability score of 4.63/5 (92.59%) and a motivation impact score of 4.54/5 (90.74%), both categorized as Very Good. These results confirm that Smart Diet Assistant effectively functions as a decision support system helping users monitor calorie intake and receive personalized diet recommendations suited to their health conditions