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Abstract

The year 2019 was the beginning of the outbreak of a disease that hit the world today called the Covid-19 Virus. The virus originated from Wuhan and is now designated as a pandemic. The main problem raised in this study is how to determine the spread of covid-19 in Indonesia based on provincial data. Because there are several areas that have high prevalence cases, it is necessary to improve health services and protocols in these areas compared to areas with rather low distribution areas. So that in this study a clustering method is needed to be able to classify data on the spread of COVID-19 in Indonesia. The algorithm used for clustering is the K-Medoids algorithm. Based on the results of the research conducted, the K-Medoids Method is able to group the Covid 19 Spreading Areas in Indonesia.

Keywords

Clustering Covid-19 K-Medoids

How to Cite

Citation Format
Husdi, & Nanja, M. (2022). Clustering Daerah Penyebaran Covid-19 di Indonesia Menggunakan Algoritma K-Medoids. Jurnal JTIK (Jurnal Teknologi Informasi Dan Komunikasi), 6(4), 608-615. https://doi.org/10.35870/jtik.v6i4.608

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Author Biographies

Husdi , Universitas Ichsan Gorontalo

Program Studi Teknik Informatika, Fakultas Ilmu Komputer, Universitas Ichsan Gorontalo

Muis Nanja, Universitas Ichsan Gorontalo

Program Studi Teknik Informatika, Fakultas Ilmu Komputer, Universitas Ichsan Gorontalo

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This is an open-access journal distributed under the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, reproduction, and adaptation in any medium (even commercially), provided appropriate credit is given to the original author(s), a link to the license is provided, and any changes made are indicated. Authors retain copyright without restrictions and grant the journal the right of first publication as well as non-exclusive publishing rights for archiving, indexing, and scholarly dissemination.

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