Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia

Research Article

Cryptocurrency Forecasting using α-Sutte Indicator, ARIMA, and Long Short-Term Memory

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  • @INPROCEEDINGS{10.4108/eai.2-8-2019.2290490,
        author={Apriliyanus Rakhmadi Pratama and Sigit Nugroho and Ketut Sukiyono},
        title={Cryptocurrency Forecasting using α-Sutte Indicator, ARIMA, and Long Short-Term Memory},
        proceedings={Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia},
        publisher={EAI},
        proceedings_a={ICSA},
        year={2020},
        month={1},
        keywords={bitcoin forecasting a-sutte indicator arima lstm},
        doi={10.4108/eai.2-8-2019.2290490}
    }
    
  • Apriliyanus Rakhmadi Pratama
    Sigit Nugroho
    Ketut Sukiyono
    Year: 2020
    Cryptocurrency Forecasting using α-Sutte Indicator, ARIMA, and Long Short-Term Memory
    ICSA
    EAI
    DOI: 10.4108/eai.2-8-2019.2290490
Apriliyanus Rakhmadi Pratama1,*, Sigit Nugroho1, Ketut Sukiyono2
  • 1: Department of Statistics, University of Bengkulu, Bengkulu 38371, Indonesia
  • 2: Department of Agricultural Economics, University of Bengkulu, Bengkulu 38371, Indonesia
*Contact email: pratama.gokilz@gmail.com

Abstract

The purpose of these studies are to obtain bitcoin price predictions using three different approach in forecasting methods : ARIMA model, α-sutte indicator and LSTM algorithm, and to find out the accuracy level of the three methods in forecasting bitcoin’s price as well. Bitcoin closing’s price each day taken from website of coin market starting from April 29 2013 to February 06 2019 was analyzed using R and Python softwares. Based on the smallest value of MSE, MAPE, and MAD, the LSTM algorithm gave the best prediction, followed by the α-Sutte indicator and the ARIMA model.