Application of Neural Network to Predict Rupiah  Exchange Rate Against Korean Won

Agung Saeful; Gifthera  Dwilestari; Ade Rizki  Rinaldi

doi:10.59934/jaiea.v4i2.734

Authors

Agung Saeful STMIK IKMI Cirebon
Gifthera Dwilestari STMIK IKMI Cirebon
Ade Rizki Rinaldi STMIK IKMI Cirebon

DOI:

https://doi.org/10.59934/jaiea.v4i2.734

Keywords:

Artificial Intelligence, Currency Exchange, Neural Networks, Prediction Accuracy, Rupiah-Korean Won

Abstract

This study investigates the application of neural networks for predicting the exchange rate of the Indonesian Rupiah against the Korean Won, addressing the challenges posed by currency fluctuations in international trade and investment. The research employs a data mining approach utilizing historical exchange rate data, which allows the neural network to identify complex patterns that traditional forecasting methods may miss. The model is developed using RapidMiner software, facilitating data preprocessing, transformation, and evaluation. The outcomes show that the predictions were quite accurate, as indicated by a low prediction error rate. The findings suggest that the neural network model not only provides reliable forecasts but also maintains consistent performance over time. This research contributes to the growing field of artificial intelligence in finance, highlighting the potential of advanced predictive models to enhance decision-making processes in the context of global economic interactions. The study underscores the importance of integrating technology with economic analysis to better navigate the complexities of currency exchange and its implications for financial risk management.

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