Abstract

In forex trading, trader has to predict the risk in forex transaction and how to gain or increase the profits based on analysis. The purpose of this study is to predict the value of the USD against the IDR by comparing the neural network method with the neural network method based on Particle Swarm Optimization (PSO) to find out which level of accuracy is higher. This method was chosen by the author after reading several previous studies using PSO-based Neural Networks showing a higher level of accuracy compared to using Neural Networks without PSO-based. From the results of the study it was found that predictions using Neural Networks strengthened with PSO resulted in very high accuracy.

Details

Title
High Accuracy in Forex Predictions Using the Neural Network Method Based on Particle Swarm Optimization
Author
Nuraeni, Nia 1 ; Astuti, Puji 1 ; Irnawati, Oky 2 ; Darwati, Ida 2 ; Danang Dwi Harmoko 2 

 Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri, Indonesia 
 Universitas Bina Sarana Informatika, Indonesia 
Publication year
2020
Publication date
Nov 2020
Publisher
IOP Publishing
ISSN
17426588
e-ISSN
17426596
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2571034656
Copyright
© 2020. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.