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

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