Visualisasi Data untuk Analisis Musik Digital Menggunakan Power BI pada Data Spotify

Authors

  • Afifah Risti Ardi Universitas Singaperbangsa Karawang
  • Apriade Voutama Universitas Singaperbangsa Karawang

DOI:

https://doi.org/10.31599/qpm0x949

Keywords:

Data Visualization, Digital Music, Power BI, Song Popularity, Spotify

Abstract

The development of digital technology has transformed the music industry with the emergence of streaming platforms such as Spotify. This study analyzes digital music data on Spotify using Power BI to identify music trends and user consumption patterns. The dataset consists of 6,300 songs with attributes such as artists, Genres, duration, popularity, and explicit status. Data visualization is employed to determine the artists with the most songs, the most popular Genres, the distribution of song duration, and the proportion of explicit and non-explicit songs. The results show that Metallica has the most songs, rock is the most popular Genre, most songs last between 2 and 6 minutes, and non-explicit songs are dominant. These findings provide insights for musicians, record labels, and streaming platform developers in designing music strategies aligned with listener preferences. 

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Published

2025-05-30

Issue

Section

Articles

How to Cite

Visualisasi Data untuk Analisis Musik Digital Menggunakan Power BI pada Data Spotify. (2025). Journal of Students‘ Research in Computer Science, 6(1), 1-10. https://doi.org/10.31599/qpm0x949