Sistem Informasi Geografis Capaian Vaksinasi Covid-19 Kabupaten Labuhanbatu Utara Berbasis Webgis Menggunakan Algoritma K-Means

Abstract

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 the
spread 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 the
vaccination program. The vaccination data is then compiled to be submitted to the North Sumatra provincial
government to be processed into information and released to the public. The absence of classification of
vaccination achievement data at the sub-district level is considered less than optimal because each sub-district is
difficult to determine whether the sub-district meets the vaccination target achievement or not. Therefore, an
algorithm called K-Means Clustering is used. K-Means Clustering is used to group data based on the similarity
of the data so that later it can be used to classify data on achievement of vaccination targets in each sub-district
in North Labuhanbatu district. The results of the classification of the data on the achievement of the vaccination
target are visualized in the form of a mapping. The mapping is realized through a web-based Geographic
Information System (GIS). The Geographic Information System of COVID-19 Vaccination in North Labuhanbatu
Regency based on Webgis is able to classify data on the achievement of COVID-19 vaccination targets in
Labuhanbatu Utara Regency using the K-Means Clustering algorithm where based on the results of the K-Means
iteration calculation, five of the eight sub-districts in North Labuhanbatu Regency North Labuhanbatu district has
met the achievement of the vaccination target.