Forecasting Bitcoin using Double Exponential Smoothing Method Based on Mean Absolute Percentage Error
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 busine...
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| Format: | Article |
| Language: | English |
| Published: |
Politeknik Negeri Padang
2020-05-01
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| Series: | JOIV: International Journal on Informatics Visualization |
| Subjects: | |
| Online Access: | http://joiv.org/index.php/joiv/article/view/335 |
| _version_ | 1818314352597401600 |
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| author | Febri Liantoni Arif Agusti |
| author_facet | Febri Liantoni Arif Agusti |
| author_sort | Febri Liantoni |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-13T08:48:17Z |
| format | Article |
| id | doaj.art-31c54eebdba1434e8129e88c05a3f4a4 |
| institution | Directory Open Access Journal |
| issn | 2549-9610 2549-9904 |
| language | English |
| last_indexed | 2024-12-13T08:48:17Z |
| publishDate | 2020-05-01 |
| publisher | Politeknik Negeri Padang |
| record_format | Article |
| series | JOIV: International Journal on Informatics Visualization |
| spelling | doaj.art-31c54eebdba1434e8129e88c05a3f4a42022-12-21T23:53:24ZengPoliteknik Negeri PadangJOIV: International Journal on Informatics Visualization2549-96102549-99042020-05-0142919510.30630/joiv.4.2.335202Forecasting Bitcoin using Double Exponential Smoothing Method Based on Mean Absolute Percentage ErrorFebri Liantoni0Arif Agusti1Universitas Sebelas Maret, IndonesiaInstitut Teknologi Adhi Tama Surabaya, IndonesiaAbstract— 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.http://joiv.org/index.php/joiv/article/view/335bitcoin, cryptocurrency, double exponential smoothing, mean absolute percentage error |
| spellingShingle | Febri Liantoni Arif Agusti Forecasting Bitcoin using Double Exponential Smoothing Method Based on Mean Absolute Percentage Error JOIV: International Journal on Informatics Visualization bitcoin, cryptocurrency, double exponential smoothing, mean absolute percentage error |
| title | Forecasting Bitcoin using Double Exponential Smoothing Method Based on Mean Absolute Percentage Error |
| title_full | Forecasting Bitcoin using Double Exponential Smoothing Method Based on Mean Absolute Percentage Error |
| title_fullStr | Forecasting Bitcoin using Double Exponential Smoothing Method Based on Mean Absolute Percentage Error |
| title_full_unstemmed | Forecasting Bitcoin using Double Exponential Smoothing Method Based on Mean Absolute Percentage Error |
| title_short | Forecasting Bitcoin using Double Exponential Smoothing Method Based on Mean Absolute Percentage Error |
| title_sort | forecasting bitcoin using double exponential smoothing method based on mean absolute percentage error |
| topic | bitcoin, cryptocurrency, double exponential smoothing, mean absolute percentage error |
| url | http://joiv.org/index.php/joiv/article/view/335 |
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