Implementasi Metode Content-Based Filtering Berbasis Android Untuk Memberikan Rekomendasi Menu Minuman

Abstract

Overchoice is a cognitive disorder in which people have difficulty making decisions when faced with many choices that make the problem in this study. This overchoice phenomenon often occurs in choosing drinks in cafes and restaurants. The purpose of this research is to create a Recommendation System (RS) to assist in choosing the drink you want to order. Making a non-personalized hospital at the Mubtada Kopi cafe uses the best rated approach and the content-based filtering method. The content-based filtering method tries to retrieve user preferences explicitly, that is asking the user to choose the preferences the user wants from the six content that has been made before then calculating the match between the user's preferences and the six contents in each item using the dot matrix formula. The results will be converted into a rating to match the best rated hospital approach which is made on a non-personalized basis. This rating indicates a match between the user's preferences and the items on the Mubtada Kopi menu list. The higher the rating, the better it matches the user's preferences. The order recommended by RS with the Content-based filtering method is rosella tea, chocolate, lemon tea, blossom tea, and spice tea