Deep Learning-Based Bitcoin Price Forecasting Using Neural Prophet

Authors

  • Teuku Rizky Noviandy Department of Informatics, Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia
  • Aga Maulana Department of Informatics, Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia
  • Ghazi Mauer Idroes Department of Occupational Health and Safety, Faculty of Health Sciences, Universitas Abulyatama, Aceh Besar 23372, Indonesia
  • Rivansyah Suhendra Department of Information Technology, Faculty of Engineering, Universitas Teuku Umar, Aceh Barat 23681, Indonesia
  • Muhammad Adam Department of Management, Faculty Economics and Business, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia
  • Asep Rusyana Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia
  • Hizir Sofyan Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia

DOI:

https://doi.org/10.60084/eje.v1i1.51

Keywords:

Bitcoin forecasting, Cryptocurrency, Deep learning, Time series, Trend analysis

Abstract

This study focuses on using the Neural Prophet framework to forecast Bitcoin prices accurately. By analyzing historical Bitcoin price data, the study aims to capture patterns and dependencies to provide valuable insights and predictive models for investors, traders, and analysts in the volatile cryptocurrency market. The Neural Prophet framework, based on neural network principles, incorporates features such as automatic differencing, trend, seasonality considerations, and external variables to enhance forecasting accuracy. The model was trained and evaluated using performance metrics such as RMSE, MAE, and MAPE. The results demonstrate the model's effectiveness in capturing trends and predicting Bitcoin prices while acknowledging the challenges posed by the inherent volatility of the cryptocurrency market.

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Published

2023-07-06

How to Cite

Noviandy, T. R., Maulana, A., Idroes, G. M., Suhendra, R., Adam, M., Rusyana, A. and Sofyan, H. (2023) “Deep Learning-Based Bitcoin Price Forecasting Using Neural Prophet”, Ekonomikalia Journal of Economics, 1(1), pp. 19–25. doi: 10.60084/eje.v1i1.51.

Issue

Vol. 1 No. 1 (2023): July 2023

Section

Articles

License

Copyright (c) 2023 Teuku Rizky Noviandy, Aga Maulana, Ghazi Mauer Idroes, Rivansyah Suhendra, Muhammad Adam, Asep Rusyana, Hizir Sofyan

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.