Measuring Corruption in Indonesia Using Fuzzy Logic
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Corruption is a phenomenon not easy to observe. Corruption theory and existing definitions are ambivalent, both in size and level. Mathematical models, and econometrics are prone to statistical errors. Fuzzy logic facilitates more humane modeling and analysis. Fuzzy logic is not bound by strong assumptions, as a solution to solve complex problems, and not precise, including corruption analysis. The main objective of this study is to measure corruption in Indonesia. The research method used fuzzy logic by specifying the Mamdani fuzzy inference system (FIS) model. FIS Mamdani was chosen because it is more human manner. Sources of secondary data used in this research from various institutions. The results show that corruption time series data can be produced. During the research year (1995-2020), corruption that occurred in Indonesia was 36.14 percent of real GDP per capita.
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