Web-Based Movie Recommendation System Using Content-Based Filtering and Cosine Similarity

Zico Fachreza Meillano; Donni Richasdy; Hasmawati Hasmawati

doi:10.24014/ijaidm.v7i1.27390

Web-Based Movie Recommendation System Using Content-Based Filtering and Cosine Similarity

Zico Fachreza Meillano, Donni Richasdy, Hasmawati Hasmawati

Abstract

Movie are one of the most popular entertainment media among people and are often chosen as activities during weekend holidays. As time goes by, world cinema continues to develop with various interesting and entertaining genres, stories and visuals. Because film is one of the entertainment media that can relieve stress from work assignments or lectures and now film production is also growing so that more and more films are being produced until finally people are confused about choosing the film they will watch. To resolve the obstacles faced, movie information is needed that can help people find movies that suit user preferences, so users need a system that can recommend movies. In this research, the author used the content-based filtering method to find movie recommendations. The substance utilizedis the movie genre. The Check Vectorization calculation is utilized to discover the term/word weight values in each record and after that these values are utilized as factors within the Cosine closeness to discover similitudes between archives.As a result of this last project the system can generate a kind of recommendations for the 10 most similar movies. The test results from this final project are that the system is running well and is reliable with an alpha test result of 100%, and a reliability test result of 0.7.

Keywords

Content-Based Filtering; Cosine Similarity; Count Vectorization; Movie Recommendation System

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DOI: http://dx.doi.org/10.24014/ijaidm.v7i1.27390

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