<![CDATA[An unbalanced diet is a major risk factor for various chronic diseases, such as obesity and hypertension. Although public awareness of nutrition has begun to increase, the phenomenon of "choice overload" in existing diet-tracking applications often makes it difficult for users to select menus that are truly healthy. This research aims to design and develop a mobile-based application named "Fit Meal," which is capable of providing personalized and filtered food menu recommendations. The application was developed using the Flutter framework to support cross-platform flexibility and integrates the Constraint-Based Filtering algorithm to filter food based on health criteria (such as the elimination of fried and junk food). Additionally, the Hybrid Data Retrieval technique is applied to optimize nutritional data searching by combining the speed of the local SQLite database with the data completeness of an external API. The test results indicate that the Hybrid method successfully improves data search efficiency, while the Constraint-Based algorithm provides accurate daily menu variations according to the user's calorie target, achieving a 100% success rate in filtering unhealthy food ingredients. Fit Meal is expected to be an effective digital solution for smartphone users in implementing a healthy diet independently and consistently.]]>
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