Sistem Informasi Geografis Capaian Vaksinasi Covid-19 Kabupaten Labuhanbatu Utara Berbasis Webgis Menggunakan Algoritma K-Means - Febriansyah Marwan; Ahmad Zakir; Eka Rahayu (Unit Pengelola Jurnal Universitas Harapan Medan, 2022)
Coronavirus Disease or COVID-19 is still a concern around the world. COVID-19 is a new disease caused by a new strain of coronavirus, Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV2). To control thespread of COVID-19, an effort is needed, namely vaccination. Meanwhile, in recording vaccination achievements,the North Labuhanbatu district government takes vaccination data from health facilities that carry out thevaccination program. The vaccination data is then compiled to be submitted to the North Sumatra provincialgovernment to be processed into information and released to the public. The absence of classification ofvaccination achievement data at the sub-district level is considered less than optimal because each sub-district isdifficult to determine whether the sub-district meets the vaccination target achievement or not. Therefore, analgorithm called K-Means Clustering is used. K-Means Clustering is used to group data based on the similarityof the data so that later it can be used to classify data on achievement of vaccination targets in each sub-districtin North Labuhanbatu district. The results of the classification of the data on the achievement of the vaccinationtarget are visualized in the form of a mapping. The mapping is realized through a web-based GeographicInformation System (GIS). The Geographic Information System of COVID-19 Vaccination in North LabuhanbatuRegency based on Webgis is able to classify data on the achievement of COVID-19 vaccination targets inLabuhanbatu Utara Regency using the K-Means Clustering algorithm where based on the results of the K-Meansiteration calculation, five of the eight sub-districts in North Labuhanbatu Regency North Labuhanbatu district hasmet the achievement of the vaccination target.