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All Journal Jurnal Nasional Teknologi Informasi dan Aplikasinya
William Soeparman
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Computer Science & IT Engineering

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Klasifikasi Musik Berdasarkan Genre Menggunakan Metode K-Nearest Neighbor William Soeparman; I Ketut Gede Suhartana
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 2 No. 2 (2024): JNATIA Vol. 2, No. 2, Februari 2024
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2024.v02.i02.p10

Abstract

Currently the amount of music in digital form continues to increase rapidly. This causes manual genre labeling of music to be inefficient. Genre labeling can be done automatically using artificial intelligence algorithms. The artificial intelligence algorithm used is an algorithm that can classify music based on genre by using the features contained in the music. This study discusses the classification of music based on genre using the K-Nearest Neighbor method or algorithm and 6 musical features, namely beat, energy, danceability, loudness, liveness, and valence. The accuracy value in this study is 54.3%. 
Co-Authors I Ketut Gede Suhartana