Skripsi

PENERAPAN SUPPORT VECTOR MACHINE PADA METODE COLLABORATIVE FILTERING UNTUK REKOMENDASI ANIME

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Penilaian

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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%.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307004441	T87098	T870982022	Central Library (REFERENS)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T870982022

Publisher

Indralaya : Jurusan Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2022

Collation

xiv, 75 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

791.43 07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Jurusan Teknik Informatika
Bioskop, Movie, Film Hiburan, Sinema

Specific Detail Info

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Statement of Responsibility

ANUG

Other version/related

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