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All Journal Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika
Fauziyah Fauziyah
Universitas Pamulang
Economics, Econometrics & Finance Mathematics

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ANALISIS KLASTER DENGAN METODE K-MEANS BERDASARKAN USIA WARGA YANG DIVAKSIN COVID-19 DI KELURAHAN GROGOL SELATAN Fauziyah Fauziyah; Choirul Basir
Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika Vol. 4 No. 1 (2024): Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/bay.v4i1.76

Abstract

COVID-19 was declared a pandemic because this virus spread throughout the world. In the context of tackling the COVID-19 virus, the Government urges the public to get vaccinated against COVID-19. Therefore, the government mobilized PKK cadres and Dasawisma cadres in collecting data on vaccinations in their respective areas. Vaccine data collection is carried out to find out the number of residents who have been vaccinated and who have not been vaccinated based on age grouping. In an effort to provide vaccinations so that there is no accumulation of residents and adjusted by the vaccine quota available at the location of the vaccine administration. Therefore, the use of the K-Means Cluster Analysis method was used to divide the data into different groups and the researchers implemented the K-Means Clustering Analysis method using manual calculations and using python language with the Google Colaboratory. The attribute used in this study is the number of residents who have been vaccinated and have not been vaccinated against COVID-19. The best results in manual calculations and Python language are 2 clusters. The most dominant cluster is Cluster 0 which consists of 8 members. The government is expected to increase the supply of vaccines because there is a lot of interest in vaccinations, especially booster vaccines
Co-Authors Choirul Basir