Forecasting the Exchange Rate of the IDR Against the USD Using the ARIMA and Exponential Smoothing Models

Lulu Yostira; Mikhratunnisa Mikhratunnisa

doi:10.30812/varian.v9i1.6144

Authors

Lulu Yostira Universitas Teknologi Sumbawa, Sumbawa, Indonesia
Mikhratunnisa Universitas Teknologi Sumbawa, Sumbawa, Indonesia

DOI:

https://doi.org/10.30812/varian.v9i1.6144

Keywords:

ARIMA, Exchange Rate, Exponential Smoothing, Forecasting, Time Series

Abstract

The exchange rate of the Rupiah against the US Dollar is one of the macroeconomic indicators that is volatile and affects economic stability. Therefore, a forecasting method that can produce accurate predictions is needed. This study aims to forecast the exchange rate of the Indonesian Rupiah against the US Dollar and compare the performance of the Autoregressive Integrated Moving average (ARIMA) and Exponential Smoothing models. The data used is monthly time series data on the exchange rate of the Indonesian Rupiah against the US Dollar from January 2001 to December 2025, obtained from the Ministry of Trade of the Republic of Indonesia. The stages of analysis in this study are data stationarity testing, determining the best ARIMA model based on parameter significance and assumption fulfillment (residuals are white noise and normally distributed), determining the best exponential smoothing model, forecasting, and evaluating the forecasting results.The results show that the best ARIMA model formed is ARIMA(3,1,3) with a MAPE value of 2.0624%, while the Exponential Smoothing model produces a MAPE value of 1.2687%. A comparison of MAPE values shows that the Exponential Smoothing model has a lower forecasting error rate than the ARIMA model. Therefore, in this study, the exponential smoothing model is considered more accurate and more suitable for forecasting the exchange rate of the rupiah against the US dollar during the research period.

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Author Biographies

Lulu Yostira, Universitas Teknologi Sumbawa, Sumbawa, Indonesia

Actuarial Science student, Sumbawa University of Technology
Mikhratunnisa, Universitas Teknologi Sumbawa, Sumbawa, Indonesia

Lecturer in the Actuarial Science program, Sumbawa University of Technology

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