Analisis Penerimaan Vaksin Covid-19 Berbasis Fuzzy Clustering Machine Learning di Provinsi Riau
DOI:
https://doi.org/10.30865/jurikom.v8i6.3636Keywords:
Clustering, Covid-19, Data Mining, Fuzzy C-Means, Silhoutte Index (SI)Abstract
Corona Virus Disease 2019 or Covid-19 is called global because it is spreading rapidly around the world, increasing cases and deaths, and lack of treatment and vaccines. Seeing rapid spread of Covid-19 and dangers will arise if not handled immediately, One of the most likely ways to prevent the spread of this virus is develop a vaccine. The Head of the Manpower and Transmigration Office of DKI Jakarta Province Issues Decree (SK) No. 1972 of 2021 concerning the Covid-19 Prevention and Control Protocol in Offices or State-Owned Enterprises. Company leaders only allow the implementation of Work From Office (WFO) to workers who have been vaccinated against Covid-19 at least the first dose. One of the companies that need vaccines for workers is PT. Perkebunan Nusantara V or PTPN V because the number of Covid-19 cases in PTPN V is increasing. Based on this case, this research will model or group Covid-19 vaccine data at PTPN V using the Fuzzy C-Means algorithm. The attributes used in this study were Gender, Age, Unit of Work and Vaccine Status. The best cluster results obtained are 5 clusters, the most cluster in cluster 2 there are 3574 persons, and the cluster which has the least number of products is cluster 4 with 18 person. The result of testing the validity of the Silhouette Index (SI) value is 0.1541, thus the quality of the cluster is still far from reaching the optimal word.
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