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Fernando Febrianto
Program Studi Informatika
Computer Science & IT

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Sistem Rekomendasi Games menggunakan Metode Item-based Collaborative Filtering berbasis Website Fernando Febrianto; Justinus Andjarwirawan; Rolly Intan
Jurnal Infra Vol 9, No 2 (2021)
Publisher : Jurnal Infra

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Abstract

Item-based Collaborative Filtering is a method that is usually used for a Recommendation System based on the items that most users choose, because this method can recommend according to the tastes of most users who choose, this method is very effective in time to recommend an item in any form.This study combines Fuzzy Similarity, Item-based Collaborative Filtering, and User-based to produce a recommendation, by calculating the similarity value using Fuzzy Similarity and User-based will make it easier to find the similarity value between users to be processed again using the Item-Based Collaborative Filtering method for recommendations that are suitable for users.The results of this study are 10 Game Recommendations that are in accordance with the implementation of Item-based Collaborative Filtering, Fuzzy Similarity, and User-based which take from the most similar people by calculating the similarity value between users and take the game that is most chosen by users. and the recommendation system works, and from the survey results, it is found that people who try to enter this website do not feel confused about the User Interface, there are also many users who like to play games, and according to the survey, the accuracy rate is quite large.
Co-Authors Justinus Andjarwirawan Rolly Intan