DESIGN AND DEVELOPMENT RESTAURANT RECOMMENDATION APPLICATION USING K-NEAREST NEIGHBORS AND CONTENT-BASED FILTERING

Abstract

The culinary business is a promising business today because food and beverages are basic needs. This can be seen from the number of cafes or restaurants in Batam City. Along with the rapid growth of the culinary business, the variety of food is becoming increasingly diverse, thus making it increasingly difficult for consumers to choose and determine the right food, both based on taste and ease of access. Therefore, it is necessary to need a system that can provide the user with the best and most suitable food or restaurant recommendations. This study designs and builds a recommendation system using K-Nearest Neighbors which functions to recommend restaurants with the closest distance, while Content-Based Filtering functions to recommend foods according to user preferences. The system is built in the form of a mobile-based application so that users can access and get more relevant recommendations. The results of the implementation of the system that was built got a pretty good response from users, where users gave a satisfaction level of 79.2% on restaurant recommendations and also 71.2% on food recommendations.