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Afridho Afnanda
Universitas Negeri Padang
Computer Science & IT Decision Sciences, Operations Research & Management Mathematics

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ANALISIS CLUSTER COVID-19 DI SUMATERA BARAT DENGAN METODE NON-HIRARKI (K-MEANS) Afridho Afnanda; Arnellis Arnellis
Journal of Mathematics UNP Vol 6, No 3 (2021): Journal Of Mathematics UNP
Publisher : UNIVERSITAS NEGERI PADANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (625.567 KB) | DOI: 10.24036/unpjomath.v6i3.11818

Abstract

COVID-19 has spread and has become a pandemic in almost all of the world, including in Indonesia. In Indonesia, this virus was first announced on March 2, 2020, until March 14 to 27, 2020, a total of 77,261 cases were identified. In an effort to stop the spread of COVID-19, the Indonesian government has made several policies that are expected to suppress the spread of this virus. Cluster analysis is a technical class, used to classify objects or cases into relatively homogeneous (same) groups called clusters. The type of data used is secondary data on COVID-19 in districts/cities of West Sumatra Province obtained from the West Sumatra Provincial Health Office and the COVID-19 task force website, where the data obtained is cumulative data from March 2020 to July 14, 2021. Optimization the number of K clusters using the elbow method to produce K=3, the results of the K-means cluster analysis with the number of K=3 concluded that the distance of members in the cluster is low and the distance between clusters is large
Co-Authors Arnellis Arnellis