Finding Features of Multiple Linear Regression On Currency Exchange Pairs

Authors

  • Raymond Sunardi Oetama Universitas Multimedia Nusantara
  • Ford Lumban Gaol Bina Nusantara University
  • Benfano Soewito Bina Nusantara University
  • Harco Leslie Hendric Spits Warnars Bina Nusantara University

DOI:

https://doi.org/10.31937/si.v13i1.2683

Abstract

Due to the prospects for financial gain, forex is always attractive to many people. However, because forex market analysis is not simple, a computer is needed to assist in creating predictions using features that are understandable to people. This study employs the Multilinear Regression technique to identify these kinds of features. The features and prediction target have a very strong correlation. With a very low RMSE and a very high R square, the prediction quality is quite outstanding. The outcome will help academics in the forex field use machine learning algorithms to make better predictions.

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Author Biography

Raymond Sunardi Oetama, Universitas Multimedia Nusantara

Fakultas Teknologi Informasi dan Komunikasi, Jurusan Sistem Informasi

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Published

2022-08-03

How to Cite

Oetama, R. S., Gaol, F. L., Soewito, B., & Warnars, H. L. H. S. (2022). Finding Features of Multiple Linear Regression On Currency Exchange Pairs. Ultima InfoSys : Jurnal Ilmu Sistem Informasi, 13(1), 46–53. https://doi.org/10.31937/si.v13i1.2683