IMPLEMENTATION OF K-MEANS ALGORITHM FOR CLUSTERING OF COVID-19 VACCINATION IN EAST JAVA WITH ORANGE

Michael Sitorus; Cornelia Antonieta DC; Cyntia Larasati

doi:10.34288/jri.v4i3.188

Authors

Michael Sitorus BRI Institute
Cornelia Antonieta DC BRI Institute
Cyntia Larasati BRI Institute

(*) Corresponding Author

DOI:

https://doi.org/10.34288/jri.v4i3.188

Keywords:

Covid-19, Vaccination, Cluster, K-Means

Abstract

Entering the era of the Covid-19 pandemic, the government has intensively implemented a vaccination program until now. Covid-19 vaccination programs are implemented to strengthen the immune system, reduce the risk of infection, reduce the severe effects of the virus, and achieve herd immunity. In the implementation, the Covid-19 vaccination is regulated by the regional government in each province with a policy that requires vaccinating Covid-19 twice for everyone with specific criteria supported by movements to wear masks, use hand sanitizers, and diligently wash hands and contact tracing of positive cases. This study aims to demographically cluster the implementation of vaccinations in all areas of East Java province in 2021. The method used in conducting this clustering is the K-Means algorithm using tools, namely Orange. From the results of the study, the results of the division or clustering of regions into three clusters were C1 for the area with the lowest vaccination, namely Pasuruan Regency, C2 for the area with moderate vaccination, namely Kediri City, and C3 for the highest vaccination area, namely Surabaya City.

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