Fuzzy-TOPSIS and the Urgency-Seriousness-Growth Scoring Technique to Determine Weights of Uncertainty Issues in School Reopening Factors During COVID-19

The decision to open schools during a pandemic is considerable controversy because it increases the risk of a spike in COVID-19 cases more quickly. However, the decision to open schools is currently based solely on national policies, which generalize opening schools in every region, potentially leading to unintended consequences during the COVID-19 crisis. This study aims to present new decision-making to rank regions determining which schools are safe to open. By focusing on problem prioritization, we integrate the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) based on a fuzzy approach and the Urgency-Seriousness-Growth (USG) scoring technique, which we call FT-USG. First, we determine the weight of the expert's argument while putting special attention on the level of urgency, seriousness, and growth of COVID-19 to the school opening issue. The fuzzy number is then calculated based on the average weight generated from the USG result. Thus, the weighted normalization computations can be executed on each factor (criteria). Then, we calculate the rankings for each alternative using the Fuzzy TOPSIS method to determine which region and school can safely reopen. To provide a comprehensive ranking that serves as a basis for decision-making, we conduct a case study to show how the suggested approach is used to address the problems.