PERBANDINGAN METODE FUZZY TIME SERIES MARKOV CHAIN DAN FUZZY TIME SERIES CHENG UNTUK PERAMALAN DATA INFLASI - Martina, Annisa; Noor Sa’adah, Fuziani; Fatchul Huda, Arief (TEKTRIKA, 2024)
The value of inflation can determine decision-making for economic actors. Therefore, in order for entrepreneursto plan their business well, accurate inflation forecasting is necessary. Fuzzy Time Series (FTS) is a concept tosolve forecasting problems if historical data is formed into linguistic values. This method has advantages, namelythe calculation process does not require a complex system and is able to solve the problem of forecasting historicaldata in the form of linguistic values. Fuzzy Time Series Cheng (FTS-Cheng) method has a slightly differentmethod of determining intervals, while the interval determination in Fuzzy Time Series Markov Chain (FTS-MC)method is the same as other FTS methods. FTS-MC is a combined method of FTS with Markov chain stochasticprocesses. In this paper, we discuss forecasting inflation data using FTS-MC and FTS-Cheng methods. This studyuses monthly data on Indonesian inflation from January 2017 to December 2021. FTS-MC method has a MAPEvalue of 9.41% and FTS-Cheng method has a MAPE value of 32.25%. Based on the criteria for the accuracy ofMAPE, the forecasting value using FTS-MC method meets the very good forecasting results and the forecastingresults using FTSC method meet the sufficient forecasting results. Based on the MAPE value obtained, a betterforecasting method for the case study of Indonesian inflation data in 2017-2022 is FTS-MC method.