Application of Double Exponential Smoothing Holt and Triple Exponential Smoothing Holt-Winter with Golden Section Optimization to Forecast Export Value of East Borneo Province

Authors

  • Novita Andriani Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Mulawarman
  • Sri Wahyuningsih
  • Meiliyani Siringoringo

DOI:

https://doi.org/10.20956/j.v18i3.17492

Keywords:

Eksport, forecasting, golden section, Holt’s double exponential smoothing

Abstract

Exponential smoothing is one of the short term forecasting methods. The selection of the forecasting method can be done by considering the type of data pattern, such as the Double Exponential Smoothing (DES) Holt method which can be used on trend patterned data and the Triple Exponential Smoothing (TES) Holt-Winter method which can be used on trend and seasonal patterned data. The main problem in using the Holt DES and Holt-Winter TES methods is the parameter selection which is usually done by trial and error, but this method takes a long time so that in this research a more efficient method is used to obtain optimal parameters, namely the golden section method. The purpose of this research was to forecast and obtain the best method for forecasting the export value of East Borneo Province. The results showed that the forecasted of export values used the Holt DES, the additive Holt-Winter TES, and the multiplicative Holt-Winter TES with golden section optimization method had a MAPE of less than 10%, which means that the forecast used these methods were very good. The best method to predict the export value of East Borneo Province was the additive Holt-Winter TES with golden section optimization method.

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Published

2022-05-15

How to Cite

Andriani, N. ., Wahyuningsih, S. ., & Siringoringo, M. . (2022). Application of Double Exponential Smoothing Holt and Triple Exponential Smoothing Holt-Winter with Golden Section Optimization to Forecast Export Value of East Borneo Province. Jurnal Matematika, Statistika Dan Komputasi, 18(3), 475–483. https://doi.org/10.20956/j.v18i3.17492

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Section

Research Articles