Analysis of the Omicron virus cases using data mining methods in rapid miner applications
Andry, J., Tannady, H., Dwinoor Rembulan, G., Freggy Dinata, D. (2023). Analysis of the Omicron virus cases using data mining methods in rapid miner applications. EKB Journal Management System, 4(2), 323-334. doi: 10.21608/mid.2023.194619.1469
Johanes Fernandes Andry; Hendy Tannady; Glisina Dwinoor Rembulan; David Freggy Dinata. "Analysis of the Omicron virus cases using data mining methods in rapid miner applications". EKB Journal Management System, 4, 2, 2023, 323-334. doi: 10.21608/mid.2023.194619.1469
Andry, J., Tannady, H., Dwinoor Rembulan, G., Freggy Dinata, D. (2023). 'Analysis of the Omicron virus cases using data mining methods in rapid miner applications', EKB Journal Management System, 4(2), pp. 323-334. doi: 10.21608/mid.2023.194619.1469
Andry, J., Tannady, H., Dwinoor Rembulan, G., Freggy Dinata, D. Analysis of the Omicron virus cases using data mining methods in rapid miner applications. EKB Journal Management System, 2023; 4(2): 323-334. doi: 10.21608/mid.2023.194619.1469

Analysis of the Omicron virus cases using data mining methods in rapid miner applications

Microbes and Infectious Diseases
Article 1, Volume 4, Issue 2, May 2023, Page 323-334  XML PDF (962.78 K)
Document Type: Original Article
DOI: 10.21608/mid.2023.194619.1469
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Authors
Johanes Fernandes Andry1; Hendy Tannady email 2; Glisina Dwinoor Rembulan3; David Freggy Dinata4
1Department of Information Systems, Universitas Bunda Mulia, Jakarta, Indonesia
2Universitas Multimedia Nusantara, Banten, Indonesia
3Department of Industrial Engineering, Universitas Bunda Mulia, Jakarta,
4Department of Engineering, Universitas Bunda Mulia, Jakarta,
Abstract
Background: Omicron has respiratory problems and pneumonia in general and specific terms. This pandemic was ravaging all countries in the world. This virus outbreak had new types to appear or so-called new variants that are still being studied by experts. Computer-assisted methods (includes smart intelligence systems, algorithms, and data mining) is key solution for detecting variants of virus.  Methods: In present study, it discussed and analyzed the omicron variant which is one of the variants of the Coronavirus 2019 (COVID-19). It’s a severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2). The emergence of this Omicron variant of COVID-19, raised more concern in the world because of its dangerous ability and the high level of spread of omicron cases. Analysis using the k-means algorithm in order to determine the level of distribution of the virus variant. Result: From the results and outputs found in this method, it is concluded that this method is used to divide the data into 3 clusters of case distribution of the Omicron variant which has been understood as a level in the distribution of cases where cluster 0 is low level, cluster 1 is high level, and cluster 2 is medium level. Conclusion: Therefore, this data mining method with special clustering and data-mining techniques give the highest number of virus distributions in which countries and divide some countries into several clusters.
Keywords
Covid-19; Omicron; Clustering; K-Means; RapidMiner
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