Interpretasi dan Visualisasi Hasil Clustering Menggunakan K-Medoid untuk Identifikasi Penyebaran Virus Covid-19

Abstract

The spread of the Covid-19 virus in Indonesia continues to occur with an increasing number. How the pattern of the virus spreads
needs to be identified to help prevent uncontrolled spread. One way to determine the pattern is to do clustering. The clustering method in this study uses the K-Medoid method, which has been used in several studies on disease analysis. Clustering results need to be processed and analyzed so that knowledge can be captured more easily. This processis called interpretation which can be supported by visualization. The interpretation process is carried out, among others, by visualizing the comparison of 2 attributes that may be related. Another process is
processing data that enters clusters by recapitulation/summing by province and other attributes by filtering and selecting records. The
interpretation results show that areas with high Population Density, Smaller Areas, High Populations indicate a higher number of cases and
new Covid-19 cases. The interpretation for each cluster of virus spread appears that cluster 1 is Big City, Cluster 2 is City of Tourism and
Neighbors with other countries, Cluster 3 is Java Island and Cluster 4 is other cities outside the other three clusters