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All Journal Journal of Mechanical Engineering Education (Jurnal Pendidikan Teknik Mesin) JOURNAL OF APPLIED INFORMATICS AND COMPUTING ILKOM Jurnal Ilmiah Jurnal Peternakan Nusantara EDUMATIC: Jurnal Pendidikan Informatika Jusikom: Jurnal Sistem Informasi Ilmu Komputer Jurnal Teknologi Dan Sistem Informasi Bisnis JIPIS Jurnal Informatika Ekonomi Bisnis JATI (Jurnal Mahasiswa Teknik Informatika) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Jurnal Teknologi Informatika dan Komputer Bulletin of Computer Science Research Brilliance: Research of Artificial Intelligence Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Lentera Pengabdian VIDHEAS: Jurnal Nasional Abdimas Multidisiplin
muhidin, asep
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Grouping the spread of the covid-19 virus based on the positive case number, population and area width using the k-means clustering method Muhidin, Asep; Danny, Muhtajudin; Rivali, Elkin
ILKOM Jurnal Ilmiah Vol 13, No 3 (2021)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i3.1011.314-321

Abstract

The spread of the Covid-19 virus began to enter Indonesia in early 2020. Until now, the spread of the virus is still occurring in several parts of Indonesia, although it has begun to decline in many areas. ). The possibility of direct human contact depends on the number of confirmed positives, the population and the area. Therefore, this study looks for the characteristics of the city/district area group based on the population, area and number of residents who are confirmed positive for the Covid-19 virus using the K-Means Clustering method. The clustering process begins with finding the best number of clusters (K) using the elbow method and testing cluster members using the silhouette and davies-bouldin index methods. The best K value results obtained by the elbow method are 3 clusters (K=3). The results of K-Means Clustering with 3 clusters show that in cluster 1, a city or district with a small area with a large population, the number of positive COVID-19 residents is large. In cluster 2, a city or district with a small area, with a moderate population, the number of people who are positive for COVID-19 is small. And in cluster 3, a city or district with a large area, with a very small population, the number of positive COVID-19 residents tends to be moderate.
Co-Authors . Ermanto Abdul Halim Anshor Ahmad Syukron Ardhi, Hendra Yunianto Baehaqi Butsianto, Sufajar Danny, Muhtajudin Dede Kardaya Deden Sudrajat Dendy K. Pramudito Dodit Ardiatma Dwi Prasetyo, Novian Edi Triwibowo Effendi, M. Makmun Eko Budiarto, S.Kom., M.M Eko Putra, Fibi Elkin Rilvani Elkin Rivalni Ermanto Fikri, Chairul Forsia, Lastry Hidarini, Silviana Fitria Hutauruk, Basar Maringan Ibnu Mubarak Indah kurniawati, Indah Jamal, Akhiratul Latifah Nurhasanah, Reka Hani M. Syaibani Anwar, S.Si., M.M Miyanti, Violi Muhammad Noor, Ridwan Adam Muhtajuddin Danny Naya, Candra Nurhadi Surojudin Pamungkas, Panji Putra Purwani Setyaningrum, Retno Putra, Fibi Eko Ramadhan, Aldi Riski Eko Ardianto Rivali, Elkin Setyaningrum, Retno Purwani Setyaningrum Setyawan, Wisnu Siswandi, Arif Surojudin, Nurhadi Tri Ngudi Wiyatno Triwibowo, Edi Wisnu Setyawan Yusmadi, Yudies Zaenal Abidin, Zihan