ANALISIS CLUSTERING GENRE MUSIK DENGAN MENGGUNAKAN ALGORITMA K-MEANS

Abstrak

Abstract
Music is a necessity that can not be separated from human life. Music is divided into multiple streams or
so-called genre. Every genre of music has its own characteristics and different styles.
The method used in this paper is the clustering analysis using data mining. The data used is data from
interviews and questionnaires. The data collected processed with Weka tool and then analyzed using KMeans algorithm. In this study conducted testing with 200 samples, 9 genre of music (Pop, Rock, Jazz,
Blues, R & B, Classical, Reggae, Keroncong, Dangdut) and 3 attributes (Quality, Satisfaction, Loyalty).
This research resulted in five clusters. The cluster of five can be concluded that the average value of the
highest quality is a genre of Pop music that is equal to 67. In terms of satisfaction Pop,Dangdut and RnB
music genre is the highest with an average value of 15. In terms of loyalty music genres Blues, Classical
and Rock is the most excellent among other music genres with an average value of 9.