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The research aim is constructing Adaptive Neuro-Fuzzy Inference System (ANFIS) model for forecasting time series data. The ANFIS model is constructed and applied to chili price data in Semarang. The daily data are written during December 2018 to May 2019. The input selection in ANFIS is done by using the Lagrange Multiplier (LM) test. The lag-1 with 2 membership functions is selected as optimal input. The performance of prediction based on in-sample data is measured by the values of mean absolute percentage error (MAPE) and root mean squares error (RMSE). The values of MAPE and RMSE are 2.9% and 939.8 respectively.

Construction of ANFIS Model Based on LM-Test for Forecasting of Chili Price Data in Semarang