Investment Decision on Cryptocurrency: Comparing Prediction Performance Using ARIMA and LSTM

Authors

  • Svend Pasak Bina Nusantara University, Indonesia
  • Riyanto Jayadi Bina Nusantara University, Indonesia
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DOI:

https://doi.org/10.51519/journalisi.v5i2.473

Keywords:

Cryptocurrency, forecast, accuracy, ARIMA, LSTM

Abstract

The increasing popularity of cryptocurrencies as a means of financial inclusion for investment and trade has become a major concern for individuals seeking to benefit from the cryptocurrency market. This study aims to provide insights for cryptocurrency investors, financial sector professionals, and academics by utilizing machine learning techniques such as ARIMA and LSTM to compare the accuracy of modeling performance on datasets predicting the prices of five cryptocurrencies, namely Bitcoin, Ethereum, Binance Coin, Tether, and Cardano. Data was obtained by downloading from the Yahoo Finance website using Jupyter notebook. The LSTM method outperformed the ARIMA method, achieving a lower MAPE value of less than 10 percent and effectively capturing price movements, providing valuable information for decision-making.

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Published

2023-05-12

Issue

Vol. 5 No. 2 (2023): Journal of Information Systems and Informatics

Section

Articles

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How to Cite

[1]
S. Pasak and R. Jayadi, “Investment Decision on Cryptocurrency: Comparing Prediction Performance Using ARIMA and LSTM”, journalisi, vol. 5, no. 2, pp. 407–427, May 2023, doi: 10.51519/journalisi.v5i2.473.