Evaluation of Support Vector Regression Methods in Predictions Bitcoin’s Close Price

Authors

  • Wulan Septya Zulmawati Universitas Negeri Padang
  • Nonong Amalita
  • Syafriandi Syafriandi
  • Admi Salma

DOI:

https://doi.org/10.24036/ujsds/vol1-iss5/121

Keywords:

Bitcoin, Cryptocurrency, Grid Search, Prediction, Support Vector Regression

Abstract

Cryptocurrency provides the most return compared to other investment instruments, causing many novice traders to be attracted to crypto as a tool to make significant profits in the short term. One of the most widely used cryptocurrencies is Bitcoin. Trading is closely related to technical analysis. Various techniques in technical analysis cause beginner traders to have difficulties choosing the right technique. Machine learning methods can be an alternative to overcoming the barriers of beginner traders in the crypto market with predictive methods. One method of machine learning for prediction is Support Vector Regression (SVR). Using the grid search algorithm shows that this method has a good predictive accuracy value of 99,25% and MAPE 0,1206%.

Published

2023-11-30

How to Cite

Wulan Septya Zulmawati, Nonong Amalita, Syafriandi Syafriandi, & Admi Salma. (2023). Evaluation of Support Vector Regression Methods in Predictions Bitcoin’s Close Price. UNP Journal of Statistics and Data Science, 1(5), 488–495. https://doi.org/10.24036/ujsds/vol1-iss5/121

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