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Erschienen in: Quality & Quantity 3/2022

03.06.2021

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

verfasst von: Dahlan Abdullah, S. Susilo, Ansari Saleh Ahmar, R. Rusli, Rahmat Hidayat

Erschienen in: Quality & Quantity | Ausgabe 3/2022

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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.

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Metadaten
Titel
The application of K-means clustering for province clustering in Indonesia of the risk of the COVID-19 pandemic based on COVID-19 data
verfasst von
Dahlan Abdullah
S. Susilo
Ansari Saleh Ahmar
R. Rusli
Rahmat Hidayat
Publikationsdatum
03.06.2021
Verlag
Springer Netherlands
Erschienen in
Quality & Quantity / Ausgabe 3/2022
Print ISSN: 0033-5177
Elektronische ISSN: 1573-7845
DOI
https://doi.org/10.1007/s11135-021-01176-w

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