Forecasting the Export Value of West Sumatra Province Using the Autoregressive Integrated Moving Average Method

Authors

  • Faddiah Gusti Handayani Universitas Negeri Padang
  • Fadhilah Fitri Universitas Negeri Padang
  • Dina Fitria Universitas Negeri Padang

DOI:

https://doi.org/10.24036/ujsds/vol4-iss1/445

Keywords:

ARIMA, Export, Forecasting, Time Series, West Sumatra

Abstract

 

The export sector in Indonesia is a key driver of national economic growth, particularly through increased foreign exchange earnings and regional development. West Sumatra is one of the provinces that notably contributes to the country's export performance due to its abundant natural resources. This research aims to forecast export values for the upcoming 16 months, spanning from September 2025 to December 2026. The study employs the ARIMA method, which is suitable for various time-series patterns, including those involving non-stationary data. Based on the analysis, the ARIMA (3,1,0) model is identified as the most suitable, achieving a MAPE of 3.90%. The forecast indicates a slight downturn from August to September 2025, followed by a steady upward trend through December 2026, reflecting a stable and positive export outlook. The findings of this research are expected to provide valuable insights for local governments and industry stakeholders in designing more effective export policies.

Published

2026-02-28

How to Cite

Faddiah Gusti Handayani, Fadhilah Fitri, & Dina Fitria. (2026). Forecasting the Export Value of West Sumatra Province Using the Autoregressive Integrated Moving Average Method. UNP Journal of Statistics and Data Science, 4(1), 34–41. https://doi.org/10.24036/ujsds/vol4-iss1/445

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