Authors:

Putu Rikky Mahendra Prasetya, Gst. Ayu Vida Mastrika Giri

Abstract:

“The development of technology in the current era in the field of multimedia, music is not just entertainment or pleasure. Nowadays, online music growth is greatly increasing, namely, music can be classified by genre. The music genre is the grouping of music according to their resemblance to each other. In previous studies, the system was built with Naive Bayes Classifier which is useful for predicting songs based on the lyrics of the song. In our study, we used a dataset that was divided into several genera, namely Blues, Electronic, R & B, Christian, Hip Hop / Rap, Rock, Country, Jazz, Ska, Dance, Pop, and Soul which obtained the accuracy of Music Content of 45 % while for Context Users get an accuracy of 60%. Keywords : Genre, Naive Bayes, Music Content, User Context”

Keywords

: Genre, Naive Bayes, Music Content, User Context

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PDF:

https://jurnal.harianregional.com/jlk/full-51893

Published

2020-01-08

How To Cite

PRASETYA, Putu Rikky Mahendra; MASTRIKA GIRI, Gst. Ayu Vida. Comparison of Use of Music Content (Tempo) and User Context (Mood) Features On Classification of Music Genre.JELIKU (Jurnal Elektronik Ilmu Komputer Udayana), [S.l.], v. 8, n. 2, p. 191-198, jan. 2020. ISSN 2654-5101. Available at: https://ojs.unud.ac.id/index.php/JLK/article/view/51893. Date accessed: 28 Aug. 2025. doi:https://doi.org/10.24843/JLK.2019.v08.i02.p11.

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 8 No 2 (2019): Jeliku Volume 8 No 2, November 2019

Section

Articles

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