The application of K-means clustering for province clustering in Indonesia of the risk of the COVID-19 pandemic based on COVID-19 data

Dahlan Abdullah (), S. Susilo, Ansari Saleh Ahmar (), R. Rusli () and Rahmat Hidayat ()
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Dahlan Abdullah: Universitas Malikussaleh
S. Susilo: Universitas Muhammadiyah Prof. Dr. Hamka
Ansari Saleh Ahmar: Universitas Negeri Makassar
R. Rusli: Universitas Negeri Makassar
Rahmat Hidayat: Department of Information Technology

Quality & Quantity: International Journal of Methodology, 2022, vol. 56, issue 3, No 18, 1283-1291

Abstract: Abstract This study was conducted with the aim to the clustering of provinces in Indonesia of the risk of the COVID-19 pandemic based on coronavirus disease 2019 (COVID-19) data. This clustering was based on the data obtained from the Indonesian COVID-19 Task Force (SATGAS COVID-19) on 19 April 2020. Provinces in Indonesia were grouped based on the data of confirmed, death, and recovered cases of COVID-19. This was performed using the K-Means Clustering method. Clustering generated 3 provincial groups. The results of the provincial clustering are expected to provide input to the government in making policies related to restrictions on community activities or other policies in overcoming the spread of COVID-19. Provincial Clustering based on the COVID-19 cases in Indonesia is an attempt to determine the closeness or similarity of a province based on confirmed, recovered, and death cases. Based on the results of this study, there are 3 clusters of provinces.

Keywords: COVID-19; Clustering; K-means clustering (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s11135-021-01176-w

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