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Abstract
The rising of bitcoin’s user as a digital currency and investments causing an instability and an uncertainty in price movement and increasing the risk of trading, therefore in this study we try to forecast the future value of bitcoin price using ARIMA Models. 2 candidate models are selected by the lowest value of AIC and using the performance indicators ME, RSME, MAE, MPE, and MAPE conclude ARIMA (1,1,0) are the best ARIMA model, then the next 5 months future price forecasted using the best model. While ARIMA (1,1,0) is the best model, the model failed to follow price movement as shown in the forecasted price.
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Copyright (c) 2022 Apriliyanus Rakhmadi Pratama

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References
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References
A. M. Antonopoulos, Mastering Bitcoin, vol. 50, no. 4. 2016. [Online]. Available: https://www.bitcoinbook.info/
O. Lopez and E. Livni, “In Global First, El Salvador Adopts Bitcoin as Currency,” The New York Times, 2021. https://www.nytimes.com/2021/09/07/world/americas/el-salvador-bitcoin.html (accessed Dec. 09, 2021).
G. E. P. Box, G. M. Jenkins, G. C. Reinsel, and G. M. Ljung, Time Series Analysis: Forecasting and Control, 5th ed. Canada: John Wiley & Sons, Inc., Hoboken, New Jersey, 2016.
G. E. Box and D. R. Cox, “An analysis of transformations,” Journal ofthe Royal Statistical Society, Series B, vol. 26, pp. 211–252, 1964, doi: 10.1080/01621459.1982.10477788.
W. W. S. Wei, Time Series Analysis: Univariate and Multivariate Methods, 2nd ed. Greg Tobin, 2006.
R. J. Hyndman and G. Athanasopoulos, “Forecasting: Principles and Practice (2nd ed),” OTexts: Melbourne, 2018. https://otexts.com/fpp2/ (accessed Jul. 06, 2022).
H. Akaike, “A New Look at the Statistical Model Identification,” IEEE Transactions on Automatic Control, vol. 19, no. 6, pp. 716–723, 1974, doi: 10.1109/TAC.1974.1100705.
R. Medar, V. S. Rajpurohit, and B. Rashmi, “Impact of Training and Testing Data Splits on Accuracy of Time Series Forecasting in Machine Learning,” 2017 International Conference on Computing, Communication, Control and Automation, ICCUBEA 2017, 2018, doi: 10.1109/ICCUBEA.2017.8463779.