Healthy Meal Recommendation Application Based on Calorie Intake Using the Knapsack Algorithm

Abstract

This study aims to develop a healthy meal recommendation application capable of generating optimal menu combinations based on the user’s daily calorie limit. The problem addressed is the difficulty in determining balanced and nutritious meals that align with individual caloric needs. To overcome this issue, the Knapsack algorithm is utilized to optimize menu selection by considering nutritional value as the optimization parameter and calories as the capacity constraint. The system is developed using the Ionic Framework as the user interface and SQLite as the local database for food data storage. The Knapsack algorithm is implemented to calculate and select food combinations with the highest nutritional value without exceeding the specified calorie limit. The testing results indicate that the application can provide accurate and consistent menu recommendations across various calorie input variations. These findings demonstrate that the proposed approach is effective in assisting users in managing their daily nutritional intake while maintaining caloric balance. Compared to conventional methods, this system offers a more adaptive and efficient solution and can be integrated into mobile devices as a tool for healthy meal planning. This study contributes to the development of intelligent systems that support a healthy lifestyle through personalized, calorie-based menu recommendations.