Cluster Analysis of Covid-19 Distribution Using K-Means Clustering Algorithm

Case Study: West Java Province

  • Ato Sugiharto Universitas Singaperbangsa Karawang
  • Betha Nurina Sari Universitas Singaperbangsa Karawang
  • Tesa Nur Padilah Universitas Singaperbangsa Karawang

Abstract

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.

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Published
2021-12-28
How to Cite
Sugiharto, A., Sari, B., & Padilah, T. (2021). Cluster Analysis of Covid-19 Distribution Using K-Means Clustering Algorithm. INTECOMS: Journal of Information Technology and Computer Science, 4(2), 291 - 301. https://doi.org/https://doi.org/10.31539/intecoms.v4i2.2776
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