Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal International Journal of Advanced Science Computing and Engineering
- Bhagaskara
Informatics Engineering, Faculty of Computer Science, Universitas Bina Darma, Palembang, Indonesia
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Enhancement Support Vector Regression Using Black Widow Optimization for Predicting Foreign Exchange Rate - Bhagaskara; Edi Surya Negara
International Journal of Advanced Science Computing and Engineering Vol 4, No 3 (2022)
Publisher : Excelligent Academia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (820.687 KB) | DOI: 10.30630/ijasce.4.3.96

Abstract

Prediction of foreign exchange rates is one of the time series problems that have fluctuating value movements. There are several algorithms that can make predictive models for this problem, one of which is Support Vector Regression (SVR). In this study, foreign exchange rate predictions were made using Hybrid SVR and Black Widow Optimization (BWO). This is done with the aim of improving the performance of the SVR in order to produce a better predictive model for the EUR/USD foreign exchange rate data in 2020. The results of the proposed algorithm get better performance in terms of R2, MSE, RMSE, MAE, and MAPE compared to SVR.
Co-Authors Edi Surya Negara