摘要：Automatic clustering technique and fuzzy logical relationships(ACFLR) is one of the forecasting method that used to predict time series data that can be applied in any data. Several previous studies said that this method has a good accuracy. Therefore, this study aims to compare the ACFLR methods with single exponential smoothing method and apply it to simulation data with uniform distribution. The performance of the method is measured based on MSE and MAPE. The results of the comparison of the methods showed that ACFLR has a higher forecasting accuracy than single exponential smoothing. This is evidenced by the value of MSE and MAPE of ACFLR is lower than single exponential smoothing. Keywords: Fuzzy, Forecasting, Automatic Clustering-Fuzzy Logic Relationships, Single Exponential Smoothing
其他摘要：Automatic clustering technique and fuzzy logical relationships(ACFLR) is one of the forecasting method that used to predict time series data that can be applied in any data. Several previous studies said that this method has a good accuracy. Therefore, this study aims to compare the ACFLR methods with single exponential smoothing method and apply it to simulation data with uniform distribution. The performance of the method is measured based on MSE and MAPE. The results of the comparison of the methods showed that ACFLR has a higher forecasting accuracy than single exponential smoothing. This is evidenced by the value of MSE and MAPE of ACFLR is lower than single exponential smoothing. Keywords: Fuzzy, Forecasting, Automatic Clustering-Fuzzy Logic Relationships, Single Exponential Smoothing
