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Pinem, Ryan Wijaya
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Computer Science & IT

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Klasifikasi Tingkat Penyebaran Pasien Covid-19 Berdasarkan Usia dan Wilayah Dengan Algoritma K-Means Putra, Adya Zizwan; Pinem, Ryan Wijaya; Silalahi, Sehat; Gulo, Fendianu; Liukhoto, Juan Antonio Adityo
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11603

Abstract

The Covid-19 virus is a new type of disease, the first case of covid-19 was found in Wuhan Province, China in 2019 with general symptoms such as pneumonia. This virus can grow rapidly and can cause serious infections and even death. Due to the very fast transmission of the virus, the WHO declared the Covid-19 virus a pandemic on March 11, 2020. Anyone can be infected with the covid-19 virus, from small children to the elderly. However, various ways have been done, but the cases of covid-19 continue to increase. Various ways have been done to reduce the spread of COVID-19 so that the Covid-19 virus does not spread quickly. Then data mining techniques are needed by implementing the K-Means algorithm because the K-Means algorithm can group data. In this study, 790 patient data were used for COVID-19 patients. The test resulted in 3 clusters grouped based on low, medium, and high categories with a DBI value of -0.332. In cluster 0 with a low category there are 3 districts, in cluster 1 with a medium category there is 1 sub-district, in cluster 2 with a high category, there are 6 districts. From the results of the test, it can be seen that the age susceptible to COVID-19 is 26 to 45 years.
Co-Authors Gulo, Fendianu Liukhoto, Juan Antonio Adityo Putra, Adya Zizwan Silalahi, Sehat