Authors:

William Soeparman, I Ketut Gede Suhartana

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%. Keywords: Music clasification, music genre, k-nearest neighbor”

Keywords

Music clasification, music genre, k-nearest neighbor

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References

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PDF:

https://jurnal.harianregional.com/jnatia/full-102053

Published

2024-02-01

How To Cite

SOEPARMAN, William; SUHARTANA, I Ketut Gede. Klasifikasi Musik Berdasarkan Genre Menggunakan Metode K-Nearest Neighbor.Jurnal Nasional Teknologi Informasi dan Aplikasnya, [S.l.], v. 2, n. 2, p. 319-326, feb. 2024. ISSN 3032-1948. Available at: https://jurnal.harianregional.com/jnatia/id-102053. Date accessed: 28 Aug. 2025.

Citation Format

ABNT, APA, BibTeX, CBE, EndNote - EndNote format (Macintosh & Windows), MLA, ProCite - RIS format (Macintosh & Windows), RefWorks, Reference Manager - RIS format (Windows only), Turabian

Issue

Vol 2 No 2 (2024): JNATIA Vol. 2, No. 2, Februari 2024

Section

Articles

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License