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Penerapan Fuzzy Logic dalam Sistem Rekomendasi Film: Studi Kasus Justice League (2017) Leonardo, Kevin; Saputra, M. Abdilah; Ikhlas, Junior; Marbun, Ricky Yohannes; Anaztasya, Azra Putri; Yulianto, Andik; Deli, Deli
Telcomatics Vol. 9 No. 2 (2024)
Publisher : Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/telcomatics.v9i2.9517

Abstract

Currently, the development of technology encourages service provider sites in selling and renting to streaming movies, such as: IMDb, NetFlix, and Flixster to develop more accurate recommendation systems. This study uses fuzzy logic to provide movie recommendation information. Two similarity measurement methods are used to improve the accuracy of recommendations: first, by considering similar user choices, and second, by matching similar movie genres that have been rated by users. The fuzzy sets and membership functions used in this study are Critic Score, Audience Score, Audience Count, Year. The test results show that the application created can provide movie recommendations that match the dataset used.