Restaurant Menu Recommendation System Using Hybrid Filtering in a Digital Application

Abstract

The advancement of information technology requires the culinary industry to adapt in order to improve service quality, yet Bhumi Durian Restaurant in Sleman still faces operational challenges such as long queues during peak hours and customer difficulty in selecting menu items due to the wide menu variety. This study aims to design and implement an integrated ordering system based on a multi-platform architecture equipped with an intelligent recommendation feature. The system is developed using React JS for the admin interface, Flutter for the customer mobile application, Golang as the backend API service, and MySQL for database management. Its main feature is the application of the Hybrid Filtering method, which combines Content Based Filtering and Collaborative Filtering to provide personalized and accurate menu recommendations. System functionality is evaluated using Black Box Testing, covering ordering, payment, and recommendation processes. The results show that the system functions properly and meets all testing criteria, demonstrating its effectiveness in improving operational efficiency, accelerating transactions, and enhancing customer satisfaction.