Implementation of Content Based Filtering Method in Restaurant Menu Ordering Recommendation System

Sales is one of the key factors in business. Failure to increase sales can lead to the collapse and bankruptcy of a business. Recommendation System is a system that is capable of predicting products desired by users. Personalized product recommendations effectively boost sales in a business. In this context, the recommendation system is a strategic tool to optimize the user experience and encourage further purchases. This research applies the content-based filtering method, which utilizes an item similarity-based recommendation approach. Three variables are used to determine the recommended product order: similarity value, sales quantity, and rating. Based on the trial, it was found that 77.3% of users were interested in the recommended products, while the remaining 22.7% preferred to purchase other products. Therefore, it can be concluded that the recommendation system can influence users to purchase the recommended products, thus impacting sales.