Cluster Analysis of Covid-19 Distribution Using K-Means Clustering Algorithm - Ato Sugiharto; Betha Nurina Sari; Tesa Nur Padilah (Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE), 2021)
Coronavirus disease (covid-19) has become a global concern after on January 20, 2020, three people were killed in the city of Wuhan, Hubei province, China. Covid-19 was first reported to have entered Indonesia on March 2, 2020, with two cases. This study aims to conduct a cluster analysis of the distribution of COVID-19 cases in West Java province as of April 1, 2021 with the variables of isolation, recovery, and death. By using the elbow method, the difference in SSE in each cluster, the silhouette graph, and the factoextra diagram, the optimum number of clusters is 3, the evaluation results show the Dunn index value = 0.4776, connectivity = 9.4738, and silhouette = 0.5839 (data structure reasoned). The clustering results show a good variance of 75.8%. Cluster 1 consists of 1 city/district, cluster 2 consists of 6 cities/districts, and cluster 3 consists of 20 cities/districts.