APPLICATION OF CLUSTERING ANALYSIS TO DATA DISTRIBUTION OF COVID-19 IN BENGKULU PROVINCE

  • Nurul Hidayati Statistics Study Program, Fakultas MIPA, Bengkulu University
DOI: https://doi.org/10.30598/barekengvol16iss2pp743-750
Keywords: Bengkulu, COVID-19, Clustering, Hiraerchical Clustering, K-Means

Abstract

Bengkulu Province is one of the provinces in Indonesia. Based on the results of the Population Census (SP) in September 2020, carried out by BPS, there were 2,010,670 inhabitants in Bengkulu Province. The area of ​​Bengkulu Province is 19,813 km2, consisting of 10 regencies/cities. The large area and population encourage an effort to anticipate the transmission of COVID-19 that is soaring high in Bengkulu Province. One is by grouping regencies/cities in Bengkulu Province based on several variables that characterize objects using the Clustering method. This study aimed to group districts/cities in Bengkulu Province based on several variables that characterize objects related to the spread of COVID-19 in Bengkulu Province. The method used was the clustering method. The data used in this study was secondary data about the variable of the spread of COVID-19 in Bengkulu Province from January 1, 2021, to May 31, 2021. It is accessed through the official website of the Bengkulu Province government to convey information to the public regarding the increase of COVID-19 Cases in Bengkulu Province. The grouping using the Hierarchical Clustering method obtained the best model as complete linkage, with the number of clusters K = 2 and the K-Means method with K = 2. The results obtained are good because it has relatively tiny variability within the cluster, and the value of variability in both clusters is relatively large.

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Published
2022-06-01
How to Cite
[1]
N. Hidayati, “APPLICATION OF CLUSTERING ANALYSIS TO DATA DISTRIBUTION OF COVID-19 IN BENGKULU PROVINCE”, BAREKENG: J. Math. & App., vol. 16, no. 2, pp. 743-750, Jun. 2022.
Issue
Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Section
Articles

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