Predictions of COVID-19 Spread by Using Supervised Data Mining Techniques

Abstract In the wake of outbreak new coronavirus, countries in world have fought to combat spread infection and imposed preventive measures compel population social distancing, which led a global crisis. Important strategies must be studied identified prevent control coronavirus COVID-19 disease 2019. this paper, effect on was studied, model based supervised data mining algorithms presented best algorithm suggested basis accuracy. model, three classifiers (Naive Bayes, Multilayer Perceptron J48) depended questionnaires filled out by Basra City respondents. The consisted 25 questions that covered fields most related affect prevention spread, including demographic, psychological, health management, cognitive, awareness factors. A total 1017 respondents were collected. This developed using Weka 3.8 tool. Results showed quarantine played an important role controlling disease. By comparing accuracy used, found J48.