Klasterisasi Sebaran Kasus Covid-19 Di Kota Denpasar Menggunakan Algoritme K-Means

Ida Bagus Gede Sarasvananda(1*), I Gusti Made Ngurah Desnanjaya(2), Yunita Dewi(3),

(1) STMIK STIKOM Indonesia
(2) STMIK STIKOM Indonesia
(3) STMIK STIKOM Indonesia
(*) Corresponding Author

Abstract


Various efforts have been made by the government to tackle the spread of Covid-19 in Denpasar City. Starting from creating a data collection system for Covid-19 patients and a map of the distribution of Covid-19 patients based on villages, which are updated every day and open for access to the general public. In the observations made by researchers, the Denpasar City Government needs to add efforts to organize the distribution of Covid-19 cases, by knowing the characteristics of Covid-19 patients and grouping villages based on similar characteristics so that the distinctive characteristics of each urban village group can be identified in Denpasar City. The problem that will be discussed in this research is how to cluster the distribution of Covid-19 cases using the K-means algorithm. The purpose of this proposed study is to cluster Covid-19 data using the K-Means algorithm. The clustering of the distribution of Covid-19 cases in Denpasar City was successfully carried out using the K-Means algorithm and the number of clusters used was 3, with cluster 0 (Low Cluster) of 16 villages / wards, cluster 2 (Regular Cluster) of 21 villages / wards, and cluster 1 (High Cluster) of 6 villages / wards. Cluster validity was tested using the Davies Bouldin method with the resulting value of -0.522.

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DOI: http://dx.doi.org/10.30645/j-sakti.v5i2.357

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