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All Journal Journal of Computation Science And Artificial Intelligence INFOKOM
Reza Prihandi
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Library & Information Science Neuroscience

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SISTEM REKOMENDASI MENU MINUMAN DENGAN METODE CONTENT – BASED FILTERING BERBASIS ANDROID PADA MUBTADA KOPI Kosim; Reza Prihandi
Journal of Computation Science and Artificial Intelligence (JCSAI) Vol. 1 No. 1 (2024): Journal of Computation Science And Artificial Intelligence (JSCAI)
Publisher : PT. Berkah Digital Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58468/wmdffh82

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
Implementasi Metode Content-Based Filtering Berbasis Android Untuk Memberikan Rekomendasi Menu Minuman kosim; Reza Prihandi
INFOKOM Vol. 16 No. 1 (2023): JURNAL INFOKOM
Publisher : STIKOM POLTEK CIREBON

Show Abstract | Download Original | Original Source | Check in Google Scholar

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
Co-Authors Kosim