Optimization of Interval Singh’s Fuzzy Time Series with Particle Swarm Optimization for Forecasting Consumer Price Index in Luwuk City - siswanto, Navira; Djakaria, Ismail; Arsal, Armayani (Journal of Mathematics, Computations and Statistics, 2025)
High inflation can threaten economic stability, with CPI as the main indicator to measure the inflation rate. Luwuk City experiences significant CPI fluctuations, reflecting economic uncertainty so an accurate forecasting method is needed. This research aims to apply Singh's Fuzzy Time Series (FTS) method optimised with Particle Swarm Optimization (PSO) to improve CPI forecasting accuracy. This research includes quantitative research, using secondary data obtained from monthly CPI data in Luwuk City on the official website of the Badan Pusat Statistik Kota Luwuk. The results showed that the use of PSO optimisation on Singh's FTS was able to optimise the prediction accuracy level of Singh's FTS forecasting on Luwuk City CPI data, with a MAPE value of 0.45%, where this value is less than 10% which indicates that the forecasting accuracy is very accurate.