Classification of Open Unemployment Rate in Indonesia with Mamdani Fuzzy Inference System

Abstract

Abstract Unemployment is a very common problem in developing countries such as Indonesia. One of the government’s efforts to overcome the problem is having skill training. However, the labor often faced difficulties in classifying unemployment in Indonesia. Therefore, the utilization of fuzzy logic is considered as an appropriate way to examine the state’s open unemployment rate by Mamdani method implementation. The input used in this case is the number of unemployment and labor force whereas the output of this system is the classification of open unemployment rate. Then the model output is compared to the classified data of the labor service and the result indicates that a matching percentage of 70,6 percent. It shows that the fuzzy model is able to determine the open unemployment rate in Indonesia.