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All Journal IJISTECH (International Journal Of Information System & Technology) IJISTECH
Ilham Prayudha
Informatics/Computer Science, Institut Teknologi Sumatera, Lampung
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Social Sciences

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Journal : IJISTECH

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Implementation of Algorithms For Frequent Itemset In Forming Association Rules In Movie Recommendation System Ilham Prayudha; Muhammad Habib Algifari
IJISTECH (International Journal of Information System and Technology) Vol 5, No 5 (2022): February
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v5i5.181

Abstract

A large number of movies around the world, causing a person to take a long time to find the movie they want to watch, not only that the audience will be confused to determine which movie suits their interests. A recommendation system is defined as a decision-making strategy for a user under complex information environments. From the perspective of e-commerce, the recommendation system was described as a tool that can help users decide related to user interest and preference [5]. The recommendation system is intended primarily for individuals who have no experience evaluating the number of alternative items offered, such as movie selection. This study will implement a recommendation system to form association rules from the two algorithms for frequent itemset, namely Apriori and FP-Growth
Co-Authors Algifari, Muhammad Habib