ANALISIS PENGELOMPOKAN WILAYAH PENYEBARAN COVID-19 di INDONESIA DENGAN METODE CLUSTERING MENGGUNAKAN ALGORITMA K-MEANS dan K-MEDOIDS

Abstrack - Corona virus is a disease that attacks human respiratory tract infections that are generally mild, such as flu and cough. If not treated quickly will result in death. This virus is quickly transmitted from human to human through the air and in contact. To reduce the spread of the virus, it requires clustering using the K-Means and K-Medoids algorithm, this method works to partition objects into groups. The clustering was obtained based on data on total cases, total deaths and total cures. Based on the results of this study, the K-Means algorithm is more optimal than the K-Medoids in clustering regions in Indonesia. It is proven that the best value of the Davies Bouldin Index from the K-Means algorithm is 0.158 with k = 4 and the K-Medoids algorithm is 0.806 with k = 5. The results of clustering are based on the most optimal value, namely the K-Means algorithm, showing cluster 1 Central Java and Java. East is at the top due to high case and death rates.