IMPLEMENTASI METODE COLLABORATIVE FILTERING UNTUK ANALISIS DATA BELANJA KONSUMEN BERBASIS WEBSITE (STUDI KASUS RESTORAN MYKITCHEN)

Abstract

In determining the right recommendation, of course, we need a method that can provide accurate recommendation results. The basics of determining recommendations can use ratings from one or more users. This will generate beneficial benefits, especially for parties engaged in the food and beverage industry.

The role of technology does not escape to produce the right recommendation system. By implementing the ItemBased Collaborative Filtering method, users can find out the right restaurant menu recommendations based on user ratings.

The Item-based Collaborative Filtering method is a method that uses the evaluation of one user and another user to obtain a recommendation. This is based on the assumption that the tendency of users is the same from time to time to a product. So that the system will provide feedback to users by processing the rating data. In determining menu recommendations for users, the ItemBased Collaborative Filtering method obtains an accuracy rate of 100%.