SISTEM REKOMENDASI MENU MINUMAN DENGAN METODE CONTENT – BASED FILTERING BERBASIS ANDROID PADA MUBTADA KOPI

Abstract

Overchoice is a cognitive disorder in which people have difficulty making decisions when faced with multiple choices, having too many equivalent options is very mentally draining because each option has to consider several alternatives to choose the best option. During this technological development where everyone is faced with an infinite number of choices every day, this overchoice phenomenon often occurs in everyday life such as choosing a drink at one of the café shops, therefore the Recommendation System is needed to help in choosing the drinks you want to order and to help in choosing other options. Recommendation System (RS) is a subclass of machine learning that is generally concerned with ranking or assessing products or users. These recommendations pertain to the decision-making process, such as what items to buy, what music to hear, or what online news to read. In this study, researchers propose to build a non-personalized hospital at the Mubtada Kopi café with the best rated approach and content-based filtering techniques. The content – based filtering technique will try to take user preferences explicitly, namely asking users to choose the preferences that users want from the 6 previously created content and then calculating the match of user preferences with the 6 contents on each item using the dot matrix formula. After getting the results, the number will be changed to a rating to match the RS approach, which is best rated which is made non-personalized. This rating is an indication of the compatibility of user preferences with the items on the Mubtada Kopi menu list. The larger the rating, the more it matches the user's preferences