BI Rate Forecasting Using the Fuzzy Time Series Method with Percentage Change as the Universe of Discourse - Felisya, Nadhira Shafa; Parmikanti, Kankan; Sukono (International Journal of Business, Economics, and Social Development, 2026)
BI Rate is a policy interest rate that reflects the direction of Bank Indonesia’s monetary policy and has a significant impact on financial sector stability and overall economic conditions. The fluctuating movement of BI Rate necessitates the use of forecasting methods capable of accurately capturing data patterns. This study aims to forecast BI Rate using the Fuzzy Time Series method with percentage change as the universe of discourse. BI Rate data from January 2009 to September 2025 are used as historical data in the forecasting process. The research stages include transforming the data into percentage change form, constructing the universe of discourse, determining main intervals and sub-intervals, performing fuzzification, establishing fuzzy logic relationships, and conducting defuzzification to obtain forecasting results. The forecasting process forms 9 main intervals and 13 sub-intervals. The forecasting accuracy is evaluated using the Mean Absolute Percentage Error (MAPE), resulting in a value of 1.56%, indicating that the Fuzzy Time Series method with the percentage change approach performs well in forecasting BI Rate and is suitable as an alternative method for policy interest rate forecasting.