@thesis{thesis,
		author={Karmila  Sely and Kusuma  Dine Tiara and Saragih  Parningotan},
		title ={PENDEKATAN PARTITIONING AROUND MEDOIDS (PAM) DALAM PENGELOMPOKAN GENRE MUSIK},
		year={2017},
		url={http://156.67.221.169/4499/},
		abstract={Music consists of many genres or subgenres, and it making difficult to
set up a standard protocol system for standardizing or grouping a music genre if
only use a subjective judgments. This research will discuss clustering music
genre using PAM clustering technique (partitoning around medoids). The
problem solving in this study will be using the "Muster" (Music Clustering)
application, which is built using Matlab R2017 and making average energy (AE),
tempo, time signature as parameter indicator and dividing as many as 5 clusters
on PAM processing system built. After that it was tested three times experiment
on Muster application, that is 10, 20 and 50 music data, and yielded accuracy
level respectively 90%, 60% and 68%, so total accuracy of PAM in grouping
music genre equal to 72.66%.}
		}