@article{Saputri_Putra_Larasati_2022, place={Purwokerto}, title={IMPLEMENTATION OF THE K-MEANS CLUSTERING ALGORITHM FOR THE COVID-19 VACCINATED VILLAGE IN THE UJUNG PADANG SUB-DISTRICT}, volume={3}, url={https://jutif.if.unsoed.ac.id/index.php/jurnal/article/view/165}, DOI={10.20884/1.jutif.2022.3.2.165}, abstractNote={<p><em>The grouping of villages vaccinated against Covid-19 in Ujung Padang District will produce several village groups with the same characteristics in each group, but there is no technology that is capable of assisting the work of the sub-district office staff in grouping villages vaccinated against Covid-19. carry out data collection, as a submission for the next Covid-19 vaccination submission/request so that it is appropriate and can help make the Covid-19 vaccination program successful in Indonesia in sub-districts. This research method was carried out by applying data mining techniques and using the k-means clustering algorithm method. Tests were carried out using Microsoft Excel, rapidminer application, and PHP programming language with MySQL as the database. The results of this study were 3 clusters consisting of C1 at the village level vaccinated with the highest Covid-19, there are 2 nagori, C2 at the village level being vaccinated against Covid-19, while there are 12 nagori and C3 at the village level vaccinated with Covid-19, there were 6 nagori. This study concluded that the k-means clustering algorithm can be used to make it easier to classified the vaccinated villages of Covid-19 on Ujung Padang sub-district.</em></p>}, number={2}, journal={Jurnal Teknik Informatika (Jutif)}, author={Saputri, Dewi Sinta and Putra, Guntur Maha and Larasati, Mustika Fitri}, year={2022}, month={Apr.}, pages={261–267} }