Rahayuningtyas, Evi Febrion and Wicaksono, Galih Wasis and Chandranegara, Didih Rizki (2021) Prediction of Yuan to IDR Exchange Rate using General Regression Neural Network. In: 2021 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE). IEEE, IEEEXplore. ISBN 978-1-6654-0148-7
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Abstract
The exchange rate is the value or price of a currency in front of other currencies divided into selling rates and buying rates. The differences and alteration of exchange rates are caused by interest rates, inflation, and many other factors. The General Regression Neural Network method is applied to build a prediction system for the Yuan to IDR exchange rate, using the input to determine the output. The dataset is taken from the Bank Indonesia website with 191 records after pre-processing. Based on the resulting test, we found that the MSE score is 106.13, the RMSE score is 10.30, and the MAE score is 8.73. The model can find and recognize training data patterns to provide excellent data output with the results given.
Item Type: | Book Section / Proceedings |
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Keywords: | prediction; exchange rate; general regression neural network. |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Engineering > Department of Informatics (55201) |
Depositing User: | galih.w.w Gali Wasis Wicaksono,S.Kom |
Date Deposited: | 15 Mar 2024 02:07 |
Last Modified: | 15 Mar 2024 02:07 |
URI: | https://eprints.umm.ac.id/id/eprint/4807 |