Evaluasi Hasil Pengujian Tingkat Clusterisasi Penerapan Metode K-Means Dalam Menentukan Tingkat Penyebaran Covid-19 di Indonesia

Authors

  • Elsa Virantika Universitas Amikom Yogyakarta, Yogyakarta
  • Kusnawi Kusnawi Universitas Amikom Yogyakarta, Yogyakarta
  • Joang Ipmawati Universitas Nahdlatul Ulama, Yogyakarta

DOI:

https://doi.org/10.30865/mib.v6i3.4325

Keywords:

Data Mining, K-Means Algorithm, Spreading, Clustering

Abstract

Coronavirus Diseases 2019, often known as COVID-19 is an infectious disease caused by the SARS-CoV-2 virus. Indonesia has a large area so that it is easy to contract COVID-19 and the spread of the Covid-19 virus in Indonesia is growing quite rapidly. Based on the region in Indonesia, it can be grouped into parts of the provinces in Indonesia and generate provincial points for the distribution of Covid-19 cases, aiming to create a strategy for handling the spread of COVID-19 in all provinces in Indonesia. The grouping of the level of spread of COVID-19 is carried out using a data mining method, namely the k-means clustering algorithm by grouping data into several clusters based on the similarity of the data. Based on the results of the study, 3 clusters were identified, namely cluster 0 with a low level of distribution of Covid-19, 12 provinces, cluster 1 with a moderate level of distribution of COVID-19, 18 provinces, and cluster 2 with a high level of distribution of COVID-19, 4 categories. province. Based on the results of this study, it is hoped that it can provide information and support the government to make strategic decisions in each cluster to reduce the level of spread of COVID-19 in Indonesia.

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Published

2022-07-25

Issue

Vol. 6 No. 3 (2022): Juli 2022

Section

Articles

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