Penerapan Data Mining Pengelompokkan Data Vaksinasi Covid-19 Menggunakan Metode Clustering
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Leni Tri Ramadhayanti
*
STMIK Kaputama, Binjai,
Indonesia
- Relita Buaton STMIK Kaputama, Binjai, Indonesia
- Yani Maulita STMIK Kaputama, Binjai, Indonesia (*) Corresponding Author
Abstract
Vaccines are biological products containing antigens in the form of microorganisms or parts thereof or substances they produce which have been processed in such a way that they are safe, which when given to a person will cause active specific immunity against certain diseases. Vaccination is a process in the body so that a person becomes immune or protected from a disease. The large number of registrants who want to vaccinate against Covid-19 at the Kebun Lada Health Center has created a large pile of vaccination data that wants to vaccinate. These data are not only inputted directly on the government website, hard copy files are only stored in a file which is then stored in a folder. Seeing this situation, of course, from these data new information can be taken which is processed using data mining techniques to dig up useful information related to vaccination data. Data mining can help companies explore new knowledge by processing existing data with clustering methods and using the K-Means algorithm. Similar results were obtained in clusters 1 and 2, namely addresses originating from north binjai, while in cluster 3 there were similar results with cluster 1, namely in the category of vaccine recipients, namely the general public.
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Pages: 111-114
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