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 and S., Susilo and Ansari Saleh, Ahmar and Rusli, Rusli and Rahmat, Hidayat (2021) The application of K‑means clustering for province clustering in Indonesia of the risk of the COVID‑19 pandemic based on COVID‑19 data. Quality & Quantity.

	Text (Artikel) Abdullah2021_Article_TheApplicationOfK-meansCluster.pdf Download (1MB)
	Text Peer Review K-Means QQ.pdf Download (996kB)
	Text (Korespondensi) 7 QUQU-D-21-00117.pdf Download (166kB)
	Text Turnitin The Application of K-means Clustering to the Zoning of Provinces in Indonesia.pdf Download (1MB)
	Text Ansari Reviewer_The Application of K Means Clustering.pdf Download (881kB)

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.

Item Type:	Article
Subjects:	FMIPA
Divisions:	FAKULTAS MIPA
Depositing User:	Ansari Saleh Ahmar
Date Deposited:	31 Aug 2022 23:56
Last Modified:	15 Mar 2023 12:04
URI:	http://eprints.unm.ac.id/id/eprint/24511

Actions (login required)

View Item