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ain, Annisa Tsamratul
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Computer Science & IT

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Penerapan Algoritma K-Means Clustering Untuk Pengelompokan Penyebaran Covid-19 di Provinsi Jawa Barat Mirantika, Nita; ain, Annisa Tsamratul; Agnia, Futry Diviana
NUANSA INFORMATIKA Vol. 15 No. 2 (2021)
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (501.635 KB) | DOI: 10.25134/nuansa.v15i2.4321

Abstract

Covid-19 is a new category of disease that has spread all over the world, including in Indonesia. Covid-19 is caused by a virus that causes disturbances in the respiratory system, from mild symptoms such as flu, to lung infections, such as pneumonia. The spread of covid-19 is so fast and massive, in Indonesia the total spread of covid-19 has reached 1,066,313 people and West Java province occupies the second highest position for the spread of covid-19. Therefore, it is necessary to group cities/districts in the province of West Java to create a strategy for handling the spread of COVID-19. The clustering of the spread of COVID-19 is carried out using the K-Means clustering algorithm which groups data into several clusters based on the similarity of the data and is implemented in R language application tools and by using the CRISP-DM method so that each phase in data mining is more structured and clearly defined. Based on the results of the study, there were 3 clusters, namely cluster 1 as the cluster with the highest number of Covid-19 spreads, obtained by 2 districts/cities. For cluster 2 as a cluster with a medium number of Covid-19 spreads, 5 districts/cities are obtained. And the remaining 20 districts/cities are included in cluster 3 with a smaller number of Covid-19 spreads. The results of this study are expected to support the West Java provincial government to make strategic decisions in each cluster to reduce the spread of COVID-19 in West Java.
Co-Authors Agnia, Futry Diviana Nita Mirantika