Penentuan Cluster Penyebaran Covid-19 Di Indonesia Menggunakan Metode K-Means Dan Davies Bouldin Index

Claudia, Larasvaty (2022) Penentuan Cluster Penyebaran Covid-19 Di Indonesia Menggunakan Metode K-Means Dan Davies Bouldin Index. Undergraduate Thesis thesis, Institut Teknologi Telkom Purwokerto.

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Abstract

Covid-19 is a new type of Pneumonia virus that attacks the respiratory system. This virus was first discovered in the Wuhan province of China with fast rapid transmission. The spread of the Covid-19 virus is increasing every day as known by the increasing number of Covid-19 cases that continue to increase every day especially in all provinces in Indonesia. This study aims to conduct clustering on the spread of Covid-19 in every province in Indonesia, which produces clusters or zones according to their characteristics which will later be used by the government or related agencies to map or supervise areas that are spreading Covid-19. The data used for this study was sourced from the kaggle website using 3 variables, namely: Number of Recoveries, Number of Deaths, and Number of Infected Cases for Covid-19 in Indonesia. This study uses the K-Means method and the Davies Bouldin Index. The results of the calculation of the 3 variables of the Three Variables will be clustered using the K-Means method and then the results of the cluster are calculated using the Davies Bouldin Index to see which cluster is at its most optimal based on the Davies Bouldin Index value. This study resulted that the most optimal clustering value was found in the 6-cluster experiment with a Davies Bouldin Index value of 0.158 in which there were 6 groups where the main Java island was in a separate group and outside Java was included in the Cluster_3 group. Keywords: Clustering , K-Means, Davies Bouldin Index, Covid-19

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