The Impact of Using the Association Method in Determining the Pattern of COVID-19 Symptoms in the Sumatra Province

Abstract

COVID-19 (coronavirus disease 2019) is a new type of disease caused by a coronavirus, namely SARS-CoV-2, also known as the Corona virus. The Corona virus outbreak is causing concern all over the world, including in Indonesia. Many people became paranoid as a result of the virus's widespread spread, which was followed by reports of a number of deaths among victims. The spread of the Corona virus in Indonesia has had a negative impact on all aspects of life. Because of the density of settlements and the vastness of Indonesia's territory, this virus became out of control and spread quickly. The lack of socialization in dealing with this virus has an impact on the community's understanding of the importance of following health protocols. The goal of this research is to use data mining techniques to determine the pattern of symptoms caused by the Corona virus. The Association method is used in data mining. APRIORI is a popular association method that employs a high frequency pattern. This method is expected to be used to determine how likely it is that one case has the first symptom in addition to other symptoms. The parameters Support and Confidence support whether or not the association rules are required. After obtaining the results of the multiplication of Support and Confidence, the rule with the highest multiplication result will be discovered. The rule with the highest result is used as a rule to be applied in the next case, namely "If you have cough symptoms, they will be accompanied by fever symptoms with 90% support and 90% confidence".