Peramalan Nilai Tukar Mata Uang Menggunakan Metode Nonlinear Autoregressive Exogenous Neural Network
), Wina Witanti(2), Melina Melina(3), (1) Universitas Jenderal Achmad Yani
Indonesia
(2) Universitas Jenderal Achmad Yani
Indonesia
(3) Universitas Jenderal Achmad Yani
Indonesia
Corresponding Author
DOI : https://doi.org/10.24036/voteteknika.v12i3.129132
Abstract
Nilai tukar mata uang sering kali mengalami fluktuasi atau naik turun terhadap mata uang negara lain, terutama Great Britain Pound (GBP) terhadap Indonesian Rupiah (IDR). Perubahan nilai tukar mata uang dipengaruhi oleh berbagai faktor yang berhubungan langsung (endogen) dan faktor yang tidak berhubungan langsung (eksogen). Ketika nilai fluktuasi nilai tukar mata uang melebihi ambang batas tertentu dapat berdampak negatif pada perdagangan internasional dan menghambat pertumbuhan ekonomi negara. Penelitian ini mengkaji penggunaan metode Nonlinear Autoregressive Exogenous Neural Network (NARX-NN) untuk meramalkan nilai tukar mata uang GBP/IDR dengan menambahkan faktor eksternal seperti inflasi, suku bunga, ekspor, dan jumlah uang beredar pada model peramalan dengan tujuan untuk meningkatkan keakuratan peramalan nilai tukar mata uang dengan menggunakan metode NARX-NN. Hasil dari penelitian ini menunjukkan bahwa dengan memasukkan faktor-faktor yang mempengaruhi fluktuasi nilai tukar mata uang, diperoleh hasil peramalan yang lebih baik yaitu nilai Mean Absolute Error (MAE) sebesar 33.28, Root Mean Square Error (RMSE) sebesar 53.53, dan R-Squared ( sebesar 0.99 dengan pembagian data sebanyak 80/20. Diharapkan, hasil penelitian ini dapat menjadi referensi bagi investor, akademisi, dan masyarakat dalam memaksimalkan keuntungan dan meminimalisir risiko kerugian pada kurs mata uang GBP/IDR.
Kata kunci : endogen; eksogen; nilai tukar; peramalan; NARX-NN.
Currency exchange rates often fluctuate or rise and fall against other countries' currencies, especially the Great Britain Pound (GBP) against the Indonesian Rupiah (IDR). Changes in currency exchange rates are influenced by various factors that are directly related (endogenous) and factors that are not directly related (exogenous). When the value of currency exchange rate fluctuations exceeds a certain threshold, it hurts international trade and hampers the country's economic growth. This research examines the use of the Nonlinear Autoregressive Exogenous Neural Network (NARX-NN) method to forecast the GBP/IDR currency exchange rate by adding external factors such as inflation, interest rates, exports, and money supply to the forecasting model to improve the accuracy of forecasting currency exchange rates using the NARX-NN method. The results of this study show that by including factors that affect currency exchange rate fluctuations, better forecasting results are obtained, namely the Mean Absolute Error (MAE) value of 33.28, Root Mean Square Error (RMSE) of 53.53, and R-Squared (R2) of 0.99 with a data division of 80/20. It is hoped that this research can be a reference for investors, academics, and the public in maximizing profits and minimizing the risk of loss on the GBP/IDR currency exchange rate.
Keywords: endogenous; exogenous; exchange rate; forecasting; NARX-NN.
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