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Mahfuzhin, Rafif
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Clustering Wilayah Penyerapan Vaksinasi Covid-19 Di Kabupaten Karawang Menggunakan Algoritma K-Means Clustering Mahfuzhin, Rafif; Jajuli, Mohamad; Mayasari, Rini
Jurnal Ilmiah Wahana Pendidikan Vol 10 No 4 (2024): Jurnal Ilmiah Wahana Pendidikan
Publisher : Peneliti.net

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.10530803

Abstract

The Covid-19 pandemic has caused significant impacts on health, economy, and society, both in Indonesia and particularly in Karawang. The government has implemented various policies to prevent the rapid spread of the virus. One crucial step in curbing the spread of covid-19 is the covid-19 vaccination program. Covid-19 vaccines like mRNA, CoronaVac, and AZD1222 have proven to be effective and safe in preventing the spread of covid-19 variants. However, the covid-19 vaccination program conducted in healthcare facilities across all districts has not been fully optimized due to the unavailability of vaccines. Therefore, an effort is required to streamline the distribution of vaccinations in Karawang Regency. One of the approaches that can be taken is the clustering of areas based on covid-19 vaccine uptake. The algorithm that can be utilized for clustering the vaccine uptake areas is the K-Means Clustering. In this study, the data utilized comprises 10 variables, including district names, recipients of dose 1, dose 2, dose 3, dose 4, population count, confirmed cases, probable cases, suspected cases, and close contact cases. The K-Means Clustering algorithm yielded three clusters with low, moderate, and high categories, achieving a Silhouette Coefficient evaluation score of 0.77, indicating strong structure.
Co-Authors Mayasari, Rini