IMPLEMENTATION OF THE K-MEANS CLUSTERING ALGORITHM FOR THE COVID-19 VACCINATED VILLAGE IN THE UJUNG PADANG SUB-DISTRICT

Dewi Sinta Saputri; Guntur Maha  Putra; Mustika Fitri  Larasati

doi:10.20884/1.jutif.2022.3.2.165

Dewi Sinta Saputri Program Studi Sitem Informasi, Sekolah Tinggi Manajemen Informatika dan Komputer (STMIK) Royal Kisaran, Indonesia
Guntur Maha Putra Program Studi Sitem Informasi, Sekolah Tinggi Manajemen Informatika dan Komputer (STMIK) Royal Kisaran, Indonesia
Mustika Fitri Larasati Program Studi Sitem Informasi, Sekolah Tinggi Manajemen Informatika dan Komputer (STMIK) Royal Kisaran, Indonesia

DOI: https://doi.org/10.20884/1.jutif.2022.3.2.165

Keywords: Algorithm, Clustering, K-means, MySQL, PHP, Vaccination

Abstract

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.

Downloads

Download data is not yet available.

References

F. Hudoyo, “Implementasi Web Service Pada Sistem Informasi Geografis (SIG) Peta Sebaran Data Covid-19 Berbasis Mobile Apps,” JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 8, no. 3, pp. 1278–1293, 2021, doi: 10.35957/jatisi.v8i3.1010.

R. N. Putri, “Indonesia dalam Menghadapi Pandemi Covid-19,” J. Ilm. Univ. Batanghari Jambi, vol. 20, no. 2, p. 705, 2020, doi: 10.33087/jiubj.v20i2.1010.

N. Nurhalimah, “Upaya Bela Negara Melalui Sosial Distancing Dan Lockdwon Untuk Mengatasi Wabah Covid-19,” Sekol. Tinggi Tarb. Insa. Kamil, pp. 1–6, 2020.

M. Malau, P. sariguna J. Kennedy, H. Situmorang, R. M. D. T, W. Veronica, and E. Manalu, “Manajemen Sosialisasi Vaksinasi COVID-19 Sebagai Upaya Menghentikan Pandemi,” J. Ikraith-abdimas, vol. 5, no. 1, pp. 99–104, 2022.

T. Tamara, “Gambaran Vaksinasi COVID-19 di Indonesia pada Juli 2021,” Medula, vol. 11, no. 1, pp. 180–183, 2021, [Online]. Available: http://journalofmedula.com/index.php/medula/article/view/255.

J. Dharmawan and J. Ardianto, “Pengaruh Kemutakhiran Teknologi, Kemampuan Teknik Personal Sistem Informasi, Program Pelatihan Pengguna Dan Dukungan Manajemen Puncak Terhadap Kinerja Sistem Informasi Akuntansi,” Ultim. J. Ilmu Akunt., vol. 9, no. 1, pp. 60–78, 2017, doi: 10.31937/akuntansi.v9i1.588.

M. C. Untoro, L. Anggraini, M. Andini, H. Retnosari, and M. A. Nasrulloh, “Penerapan metode k-means clustering data COVID-19 di Provinsi Jakarta,” Teknologi, vol. 11, no. 2, pp. 59–68, 2021, doi: 10.26594/teknologi.v11i2.2323.

M. W. Goni, D. Gustian, and F. Sembiring, “Implementasi K-Means Dalam Pengelompokan Penyebaran Covid-19 Di Jawa Barat,” J. Ilm. Komput., vol. 17, no. Vol 17, No 2, Agustus 2021, pp. 107–118, 2021, [Online]. Available: http://ojs.stmik-banjarbaru.ac.id/index.php/progresif/article/view/648/pdf.

M. Minarni, E. I. Sari, A. Syahrani, dan P. Mandarani, Klasterisasi Penyakit Menggunakan Algoritma K-Medoids pada Dinas Kesehatan Kabupaten Agam. J. Nas. Pendidik. Tek. Inform. 2021; Vol. 10, No. 3: 137.

Y. F. S. Y. Damanik, S. Sumarno, I. Gunawan, D. Hartama, and I. O. Kirana, “Penerapan Data Mining Untuk Pengelompokan Penyebaran Covid-19 Di Sumatera Utara Menggunakan Algoritma K-Means,” J. Ilmu Komput. dan Inform., vol. 1, no. 2, pp. 109–132, 2021, doi: 10.54082/jiki.13.

I. Parlina, A. P. Windarto, A. Wanto, and M. R. Lubis, “Memanfaatkan Algoritma K-Means Dalam Menentukan Pegawai Yang Layak Mengikuti Asessment Center,” Memanfaatkan Algoritm. K-Means Dalam Menentukan Pegawai Yang Layak Mengikuti Asessment Cent. Untuk Clust. Progr. Sdp, vol. 3, no. 1, pp. 87–93, 2018.

Z. Nabila, “Analisis Data Mining Untuk Clustering Kasus Covid-19,” J. Teknol. dan Sist. Inf., vol. 2, no. 2, pp. 100–108, 2021.

L. Gayatri and H. Hendry, “Pemetaan Penyebaran Covid-19 Pada Tingkat Kabupaten/Kota Di Pulau Jawa Menggunakan Algoritma K-Means Clustering,” Sebatik, vol. 25, no. 2, pp. 493–499, 2021, doi: 10.46984/sebatik.v25i2.1307.

U. R. Gurning and Mustakim, “Penerapan Algoritma K-Means dan K-Medoid untuk Pengelompokkan Data Pasien Covid-19,” Build. Informatics, Technol. Sci., vol. 3, no. 1, p. 48−55, 2021, doi: 10.47065/bits.v3i1.1003.