Application of Fuzzy Logic in PEOPLES Framework for Community Resilience Measurement in Flood Disaster

Abstract

Assessing community resilience is challenging due to the complexity of influencing factors. Various frameworks and models, such as the PEOPLES framework, have been developed for both theoretical and practical applications. In dealing with uncertainty, selecting the right model is crucial. While probabilistic approaches are common, they can be insufficient. Fuzzy logic, as an uncertainty model, offers a solution. This study explores community resilience in Bekasi City using fuzzification and trapezoidal membership functions for input variables categorized as low, medium, and high. The output uses triangular membership functions with four degrees: low, medium, high, and very high, ranging from 43-129. Fuzzy rule formulation applies the "minimal" function with 2,187 basic rules. The test results show high accuracy, with predictions for six regional segments matching expert assessments.