Abstract
In this paper, we propose a new method for forecasting based on automatic-optimized fuzzy time series to do forecasting on Indonesia Inflation Rate (IIR). First, we propose the forecasting model of two-factor high-order fuzzy-trend logical relationships groups (THFLGs) for predicting the IIR. Second, we propose the interval optimization using automatic clustering and particle swarm optimization (ACPSO) to optimize the interval of main factor IIR and secondary factor SF, where SF = {Customer Price Index (CPI), the Bank of Indonesia (BI) Rate, Rupiah Indonesia /US Dollar (Rp/USD) Exchange rate, Money Supply}. The main contribution of this paper, we propose a new model of fuzzy forecasting based on interval optimization with THFLGs, ACPSO, and similarity between measured subscripts from FS to do forecasting IIR. Forecasting results of the proposed method get high accuracy and better than previous methods.
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