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Mentari Tri Indah Rahmayani
Sekolah Tinggi Agama Islam Negeri Bengkalis

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Implemention K-Means Algorithm Determine the Recovery Rate of Covid-19 Patients in Indonesia Mentari Tri Indah Rahmayani; Nani Hidayati
Jurnal Mantik Vol. 6 No. 1 (2022): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jurnalmantik.v6i1.2059

Abstract

In Indonesia, the number of COVID-19 sufferers continues to increase every time, data from the Indonesian National Disaster Management (BPBN) shows the number shows the number of deaths as many as 100,636 people and the recovery rate as many as 2,907,920 people. In this study, the authors applied the k-means clustering algorithm to group the areas with the lowest cure rate (C1), moderate cure rate (C2) and high cure rate (C3). The purpose of this study is to group areas in Indonesia with the highest cure rates and to find out the similarities in data management using manual calculations and using Rapid Miner Software. The results show that from 34 provinces in Indonesia 30 provinces are in the low cluster, namely, Aceh, North Sumatra, West Sumatra, Riau, Jambi, South Sumatra, Bengkulu, Lampung, Bangka Belitung, Riau Islands, DI Jogjakarta, Banten, Bali, NTB, NTT, West Kalimantan, Central Kalimantan, South Kalimantan, East Kalimantan, North Kalimantan, North Sulawesi, Central Sulawesi, South Sulawesi, Southeast Sulawesi, Gorontalo, West Sulawesi, Maluku, North Maluku, Papua and West Papua, with a moderate cure rate cluster of 2 provinces, namely Central Java and East Java, and the cluster with the highest cure rate was 2 provinces, namely DKI Jakarta and West Java.