Classification of restrictions on community activities level in the covid-19 pandemic using fuzzy logic - Abidatul Izzah; Ratna Widyastuti; Zulfa Khalida (Institute of Computer Science (IOCS), 2023)
Indonesia is facing a second wave of Covid-19 cases in mid-2021. In that time, the increase reached 381 percent or almost 5 times. Therefore, the government announced the Enforcement of Restrictions on Community Activities. This is determined by the government for each city in Indonesia so it cannot be predicted by the general public. Actually, The Restrictions on Community Activities status level determines the risk of a region's economic activities. Therefore, we need a method that can help to categorize the level of PPKM in an area based on available daily data. Thus, this study aims to create a rule model based on Fuzzy Tsukamoto logic that can help determine the level of risk of an area. Based on data on Covid-19 patients in Malang District, East Java has formed 6 fuzzy variables, each of which has 4 fuzzy sets, and 15 rules that can be used as a classification model. From the results, we obtained an accuracy value of 80%. This shows that the generated rule can properly classify the daily Covid-19 data to then estimate the next restrictions level.