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CLUSTERING OF POPULAR SPOTIFY SONGS IN 2023 USING K-MEANS METHOD AND SILHOUETTE COEFFICIENT

Authors :
Nur Rohman
Arief Wibowo
Source :
Pilar Nusa Mandiri, Vol 20, Iss 1, Pp 18-24 (2024)
Publication Year :
2024
Publisher :
LPPM Nusa Mandiri, 2024.

Abstract

The rapid advancement of technology and globalization in this era has brought about comprehensive and easily accessible music streaming services, one of which is Spotify. According to Kompas.com, Spotify has experienced a rise in subscribers up to 130 million, as a platform that offers various features besides music streaming. Spotify also provides a better user experience and has the ability to compete with other music streaming platforms. The mission of this research is to classify popular Spotify song data in 2023, which can aid in a deeper understanding of listener preferences or music trends. Based on the test results, there were 2 clusters obtained with cluster 0 containing 863 data and cluster 1 containing 90 data. From the testing results conducted in the K-Means analysis, a Silhouette Coefficient of 0.81 was obtained, which falls into the category of Strong Structure. From these results, it can be suggested that cluster formation was done very well to provide more personalized and relevant music recommendations to Spotify platform users. By understanding the preferences and patterns of listeners revealed through clustering, streaming services can enhance user experience by providing more tailored content.

Details

Language :
English, Indonesian
ISSN :
19781946 and 25276514
Volume :
20
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Pilar Nusa Mandiri
Publication Type :
Academic Journal
Accession number :
edsdoj.47678cd226e422bb2fd70bc5c2aa254
Document Type :
article
Full Text :
https://doi.org/10.33480/pilar.v20i1.4937