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Suci Fitriani
Departement of Informatics, Universitas Malikussaleh, Aceh
Mathematics

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Clustering the Distribution of COVID-19 in Aceh Province Using the Fuzzy C-Means Algorithm Nurdin Nurdin; Suci Fitriani; Zara Yunizar; Bustami Bustami
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 6, No 3 (2022): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v6i3.8576

Abstract

COVID-19 is a virus that attacks the respiratory system in humans and spreads rapidly. The government has taken various ways to reduce the rate of transmission of COVID-19, including by providing a COVID-19 information center that can be accessed by anyone, but there is no grouping of regional zones with high to low COVID-19 cases. Therefore, a clustering process system for the spread of COVID-19 is needed so that it is able to provide information on clusters of COVID-19 distribution areas in Aceh with the highest case zone (red zone), medium case zone (yellow zone), and low case zone (green zone). The steps carried out in this study using the Fuzzy C-Means Algorithm are collecting data (input data), conducting the clustering process (determining the number of clusters, weighting rank, maximum iteration and epsilon), displaying clustering results. In this study, the authors collected COVID-19 data from 23 districts/cities in Aceh using 6 variables consisting of confirmed, in care, healed, died, suspected, and probable. The results of the clustering study on the spread of COVID-19 are as follows: One district/city in cluster 1 (red zone), the four districts/cities in cluster 2 (yellow zone), eighteen districts/cities in cluster 3 (green zone). Based on the results of this study, the Fuzzy C-Means Algorithm can be used and applied properly in clustering the spread of COVID-19 in the Province of Aceh. 
Co-Authors Bustami Bustami Nurdin Nurdin Zara Yunizar