• Silvi Ana Universitas Islam Negeri Sultan Syarif Kasim Riau
  • Rahmad Kurniawan
  • Alwis Nazir


Coronavirus disease 2019 (COVID-19) is a new type known to infect humans in December 2019. COVID-19 cases have spread throughout the world, including in Indonesia. Riau Province is one of the provinces with a fairly high number of COVID-19 cases. Appropriate mitigation measures are needed to prevent the COVID-19 outbreak. Based on a literature review, COVID-19 outbreaks are infected based on the closest distance. Epidemiologists have also used the clustering method to group the areas affected by the COVID-19 pandemic. Therefore, this study applied the one-hot encoding technique and the k-means clustering algorithm to cluster regions with similar data characteristics. Twelve districts in Riau with seven features were obtained for clustering. Based on the experimental testing results, three clusters were obtained, namely C1 (Pekanbaru, Kampar), C2 (Siak, Bengkalis, Rokan Hulu, Kuantan Singingi), and C3 (Dumai, Indragiri Hilir, Indragiri Hulu, Pelalawan, Rokan Hilir, Meranti). The results of the cluster were tested with a silhouette score of 0.6. Thus, it can be concluded that the one-hot encoding technique and the k-means clustering algorithm have the potential to be used to cluster areas of the COVID-19 pandemic based on similar data characteristics.


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How to Cite
S. Ana, R. Kurniawan, and A. Nazir, “PENGKLASTERAN RISIKO COVID-19 DI RIAU MENGGUNAKAN TEKNIK ONE HOT ENCODING DAN ALGORITMA K-MEANS CLUSTERING”, Jurnal Informasi dan Komputer, vol. 10, no. 1, pp. 154-163, Apr. 2022.