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All Journal (JELIKU) Jurnal Elektronik Ilmu Komputer Udayana
Prasetya, Putu Rikky Mahendra
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Computer Science & IT

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Comparison of Use of Music Content (Tempo) and User Context (Mood) Features On Classification of Music Genre Prasetya, Putu Rikky Mahendra; Mastrika Giri, Gst. Ayu Vida
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 2 (2019): Jeliku Volume 8 No 2, November 2019
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2019.v08.i02.p11

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
Co-Authors Gst. Ayu Vida Mastrika Giri