PENERAPAN SUPPORT VECTOR MACHINE PADA METODE COLLABORATIVE FILTERING UNTUK REKOMENDASI ANIME

WAHYUNINGTYAS, RINI and Samsuryadi, Samsuryadi and Rachmatullah, Muhammad Naufal (2022) PENERAPAN SUPPORT VECTOR MACHINE PADA METODE COLLABORATIVE FILTERING UNTUK REKOMENDASI ANIME. Undergraduate thesis, Sriwijaya University.

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Abstract

The increasing number of anime productions with various genres makes it difficult for users to find anime to watch. According to the problems, a recommendation system is needed to provide anime according to the genre preferred by users. The challenges are in the form of data with large dimensions and uneven distribution generating low accuracy and the system running slowly. In order to solve the problem, this research combines collaborative filtering and support vector machines (SVM). The SVM method is used to classify user “likes” and “dislikes”, then the data labeled “dislike” will be deleted to ease the work of the system. Experiment on MyAnimelist data shows higher recommendation results. The test results for the SVM model obtained an accuracy of 93.29%, a precision of 94.07%, and a recall of 98.98%. The test results of the recommendation system by applying the SVM method provide an accuracy rate of 70.25%, a precision of 86.65%, and a recall of 67.32%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Machine Learning, Sistem Rekomendasi, Anime, Support Vector Machine, Collaborative Filtering
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics > Q325.5 Machine learning
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Rini Wahyuningtyas
Date Deposited:	20 Jan 2023 04:18
Last Modified:	20 Jan 2023 04:18
URI:	http://repository.unsri.ac.id/id/eprint/87098

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