Peramalan Menggunakan Time Invariant Fuzzy Time Series

Siti Rahmah Binaiya (Laboratorium Statistika Ekonomi dan Bisnis FMIPA Universitas Mulawarman)
Memi Nor Hayati (Laboratorium Statistika Terapan FMIPA Universitas Mulawarman)
Ika Purnamasari (Laboratorium Statistika Ekonomi dan Bisnis FMIPA Universitas Mulawarman)

Eksponensial
Vol 10 No 2 (2019)

Forecasting is a technique for estimating a value in the future by looking at past and current data. Fuzzy Time Series is a forecasting method that uses fuzzy principles as the basis, where the forecasting process uses the concept of fuzzy set. This study discusses the Time Invariant Fuzzy Time Series method developed by Sah and Degtiarev to forecast the East Kalimantan Province Consumer Price Index (CPI) in May 2018. In the Time Invariant Fuzzy Time Series method using a frequency distribution to determine the length of the interval, 13 fuzzy sets are used in the forecasting process. Based on this study, using CPI data of East Kalimantan Province from September 2016 to April 2018, the forecasting results for May 2018 were obtained 135.977 and obtained the results of forecasting error values using Mean Absolute Percentage Error (MAPE) is under 10% of 0.0949%.