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All Journal JOIV : International Journal on Informatics Visualization
Arif Agusti
Institut Teknologi Adhi Tama Surabaya, Indonesia
Computer Science & IT

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Forecasting Bitcoin using Double Exponential Smoothing Method Based on Mean Absolute Percentage Error Febri Liantoni; Arif Agusti
JOIV : International Journal on Informatics Visualization Vol 4, No 2 (2020)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (88.161 KB) | DOI: 10.30630/joiv.4.2.335

Abstract

Abstract— After being introduced in 2008, the rise in the price of bitcoin and the popularity of other cryptocurrencies triggered a growing discussion about how much energy was consumed during the production of this currency. Making cryptocurrency the most expensive and most popular, both the business world and the research community have begun to study the devel-opment of bitcoin. In this study bitcoin price predictions are performed using the double exponential smoothing method based on the mean absolute percentage error (MAPE). The MAPE value is used to find the best alpha (α) parameter as the basis for bitcoin price forecasting. The dataset used is the price of bitcoin from 2017 to 2019. The dataset was obtained from www.cryptocompare.com. As for the value of the alpha parameter (α), using a value of 0.1 to 0.9. Based on the test results using the double exponential smoothing method obtained the smallest MAPE value of 2.89%, with the best alpha (α) at 0.9. The prediction is done to see the price of bitcoin on January 1, 2020. The error rate generated on the predicted price of bitcoin uses an amount of 0.0373%. This shows that the system built can be used as a support for decision making when trading bitcoin.
Co-Authors Febri Liantoni