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All Journal International Journal of Electrical and Intelligent Engineering
Galan Ramadan Harya Galib
Universitas Islam Negeri Maulana Malik Ibrahim Malang
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Artificial Intelligence Application of Back-propagation Neural Network in Cryptocurrency Price Prediction Muhammad Sahi; Galan Ramadan Harya Galib
International Journal of Electrical and Intelligent Engineering Vol 1, No 1 (2025)
Publisher : Department of Electrical Engineering Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ijeie.v1i1.33800

Abstract

This study explores the use of Deep Learning and Artificial Intelligence (AI), particularly Artificial Neural Networks (ANN), for cryptocurrency price prediction. Given the high volatility of crypto markets, traditional models often underperform. A backpropagation-based ANN with a 7-5-1 architecture is proposed and tested using historical Bitcoin data. The model achieves high accuracy, with a Mean Squared Error (MSE) of 4.0431e-04, equivalent to 99.96% accuracy, demonstrating its ability to capture complex nonlinear patterns. However, overfitting remains a concern, emphasizing the need for robust generalization and feature selection. The results validate the potential of ANN in crypto forecasting and encourage further research using diverse features and assets.
Co-Authors Muhammad Sahi