Analysis of Song Popularity in Business Digital Music Streaming for Increasing Quality Using Kohonen SOM Algorithm

Abstract

Consumption of digital music services has grown dramatically in recent years. There is an increase in music streaming consumption from 2015 to 2016, which is 76.4%. One of the most popular music streaming services, Spotify, has experienced an increase in customers from year to year. This increase enables businessmen / music producers to increase their business profits by analyzing music / songs to find out the audio attributes that make the song enjoyable for many people. Processing and analysis data are using Kohonen SOM Algorithm. The function is to find out which audio attribute groups are most liked by Spotify users where a good music is a music that can be used as a therapy. The result is LR = 0.1, PLR = 0.9, and epoch = 70 - 500, it can be concluded that cluster 2 is the cluster that has the most number of streams with 27 songs where the smallest DBI value is obtained at epoch = 200. Thus, with the statistic analysis, the obtained information is; it is expected that businessman / music producers can increase their business profits by improving their music quality that focus on songs with modes = 0 (Minor) and loudness features