Penerapan K-Means dan Fuzzy C-Means untuk Pengelompokan Data Kasus Covid-19 di Kabupaten Indragiri Hilir - Sania Fitri Octavia; Mustakim Mustakim (Building of Informatics, Technology and Science (BITS), 2021)
In the beginning of 2020 world was shocked because new virus spreaded, that is Coronavirus Disease 2019 (Covid-19). This virus spread quickly in almost country, including Indonesia. Covid-19 virus deployment started in various regions in Indonesia stay increasing everyday. this research has been done the region clustering that infected Covid-19 case in Indragiri Hilir district to inform to central government about Covid-19 handling. To do Clustering in this research used K-Means and Fuzzy C-Means Algorithm. After done some of test, it's obtained the ratio which was tested with Silhouette Index and Partition Coefficient, SI validity value of K-Means is 0,950 while PCI validity value of Fuzzy C-Means is 0,960. The results have been obtained shown that Fuzzy C-Means Method is the best Method to do Clustering Covid-19 data in Indragiri Hilir district Because the validity value is closed to 1 which is located in K=3.