Implementation of Algorithms For Frequent Itemset In Forming Association Rules In Movie Recommendation System

Ilham Prayudha(1*), Muhammad Habib Algifari(2),

(1) Informatics/Computer Science, Institut Teknologi Sumatera, Lampung
(2) Informatics/Computer Science, Institut Teknologi Sumatera, Lampung
(*) Corresponding Author


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

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