Applying Artificial Neural Networks in Forecasting US Dollars-Indonesian Rupiah Exchange

• Main Authors: Ardiansyah, Soleh, Mazlina, Abdul Majid, Jasni, Mohamad Zain
• Format: Conference or Workshop Item
• Language: English
• Published: 2013
• Subjects: QA76 Computer software
• Online Access: http://umpir.ump.edu.my/id/eprint/5188/1/CSIT-2013_Ardiansyah_Soleh.pdf; http://umpir.ump.edu.my/id/eprint/5188/

This paper investigates artificial neural networks prediction modeling of foreign currency rates using Levenberg Marquardt (LM) learning algorithms. The models were trained from historical data using US Dollar (USD) currency rates against Indonesian Rupiah (IDR). The forecasting performance of the models was evaluated using a number of statistical measurements and compared. The results show that significant close prediction result can be made using simple architecture forecasting model. LM1 and LM6 model achieves closer prediction of the actual value than that other model.Both forecasting models attain significantly high rate of predicting correct directional change (above 80%). The effect of network architecture on the performance of the forecasting model is also presented.