Forecasting The Export Value Of Indonesian Footwear Using Arima And Fuzzy Time Series Lee Methods

Mira Zayan; Wellie Sulistijanti

doi:10.54209/infosains.v14i02.4669

Authors

Mira Zayan Faculty of Science and Technology, Muhammadiyah Institute of Statistics and Business Technology, Ngaliyan, Semarang, Indonesia
Wellie Sulistijanti Faculty of Science and Technology, Muhammadiyah Institute of Statistics and Business Technology, Ngaliyan, Semarang, Indonesia

DOI:

https://doi.org/10.54209/infosains.v14i02.4669

Keywords:

Forecasting, Export, ARIMA, Lee's Fuzzy Time Series

Abstract

Industrial sector exports have a large contribution to total exports in the Indonesian economy. A forecasting model is needed that is able to forecast the export value of the industrial sector well. The data used in this study are monthly data on the Export Value of Indonesian Footwear. The ARIMA method can forecast data well linearly but has a decrease in accuracy for data with nonlinear components. Lee's Fuzzy Time Series method is good for nonlinear data and has a level of accuracy that is easy to understand. The ARIMA method requires assumptions to be met such as the data must be stationary, then the Fuzzy Time Series Lee method can be used for non-stationary data, because the Fuzzy Time Series Lee does not require certain assumptions to be met. The results of forecasting the value of Indonesian footwear exports using ARIMA have a MAPE value of 18.5% with good criteria, the Fuzzy Time Series Lee method has a MAPE value of 18.2% with good criteria, so it can be used to forecast the value of Indonesian footwear exports for the August 2023 period of 46,563,984 USD. The forecasting results can be a reference for future policy making.

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