Article Sidebar

Download
pdf
Statistic
Read Counter : 308 Download : 258

Main Article Content

Abstract

Abstract— Memprediksi harga mata uang kripto seperti Dogecoin semakin penting seiring dengan lebih banyak investor
beralih ke aset digital sebagai sumber profit yang besar. Jurnal ini mengeksplorasi penggunaan algoritma machine
learning untuk memprediksi harga Dogecoin dan juga factor yang mempengaruhinya. Hal-hal diluar Dogecoin seperti
sesame mata uang kripto (bitcoin dan etherium), emas (XAUUSD), indeks harga dolar (DXY), dan perubahan harga
dalam % juga turut dilibatkan dalam penelitian ini. Temuan studi ini memiliki implikasi bagi investor dan analis yang
ingin memprediksi harga Dogecoin. Dengan memanfaatkan algoritma machine learning dan mempertimbangkan factor
yang mempengaruhinya, investor lebih terampil dalam membuat keputusan berdasarkan informasi tentang strategi
investasi mereka. Secara keseluruhan, studi ini menyoroti potensi machine learning dalam memprediksi apakah harga
Dogecoin akan Up (melampaui harga pembukaan di hari sebelumnya atau tidak) dengan pendekatan data yang sangat
banyak (Big Data). Hasilnya sangat memuaskan dimana dengan menggunakan pendekatan machine learning terdapat
akurasi precision (prediksi benar positif) yang tertinggi yaitu 97% dengan bantuan algoritma Neural Network.

Keywords

Kata kunci — crypto, doge, machine learning

Article Details

References

  1. [1] Narayanan, A., Bonneau, J., Felten, E., Miller, A., Goldfeder, S., & Clark, J. (2016). Bitcoin and Cryptocurrency Technologies Introduction to the book.
  2. [2] Kurka, J. (2019). Do cryptocurrencies and traditional asset classes influence each other? Finance Research Letters.
  3. [3] Klein, T., Pham Thu, H., & Walther, T. (2018). Bitcoin is not the New Gold – A comparison of volatility, correlation, and portfolio performance. International
  4. Review of Financial Analysis.
  5. [4] Kjærland, F., Khazal, A., Krogstad, E., Nordstrøm, F., & Oust, A. (2018). An Analysis of Bitcoin’s Price Dynamics. Journal of Risk and Financial Management.
  6. [5] Hossain, S. S., Oni, S. S., Mourshed, I., Ahmed, R., & Islam, T. (2017). Bitcoin and Its Impact on Financial Markets.
  7. [6] Sovbetov, Y. (2018). M P RA Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litcoin, and Monero. In Journal of
  8. Economics and Financial Analysis (Vol. 2).
  9. [7] Selmi, R., Mensi, W., Hammoudeh, S., & Bouoiyour, J. (2018). Is Bitcoin a hedge, a safe haven or a diversifier for oil price movements? A comparison with
  10. gold. Energy Economics.
  11. [8] Yermack, D. (2013). Nber Working Paper Series Is Bitcoin A Real Currency? An Economic Appraisal Is bitcoin a real currency?.
  12. [9] Tikhomirov, S. (2017). Ethereum: state of knowledge and research perspectives.
  13. [10] Ciaian, P., Rajcaniova, M., & Kancs, d’Artis. (2018). Virtual relationships: Short- and long-run evidence from BitCoin and altcoin markets. Journal of
  14. International Financial Markets, Institutions and Money.
  15. [11] Corbet, S., Meegan, A., Larkin, C., Lucey, B., & Yarovaya, L. (2017). Exploring the Dynamic Relationships between Cryptocurrencies and Other Financial
  16. Assets.
  17. [12] Ciaian, P., Rajcaniova, M., & Kancs, d’Artis. (2016a). The economics of BitCoin price formation. Applied Economics.
  18. [13] Brière, M., Oosterlinck, K., & Szafarz, A. (2015). Virtual currency, tangible return: Portfolio diversification with bitcoin. Journal of Asset Management.
  19. [14] Bouri, E., Gupta, R., Lahiani, A., & Shahbaz, M. (2018). Testing for asymmetric nonlinear short- and long-run relationships between bitcoin, aggregate
  20. commodity and gold prices. Resources Policy.
  21. [15] Feng, W., Wang, Y., & Zhang, Z. (2018). Can cryptocurrencies be a safe haven: a tail risk perspective analysis. Applied Economics.
  22. [16] Erdas, M. L., & Caglar, A. E. (2018). Analysis of the relationships between Bitcoin and exchange rate, commodities and global indexes by asymmetric causality
  23. test. In Eastern Journal Of European Studies.
  24. [17] Baumöhl, E. (2019). Are cryptocurrencies connected to forex? A quantile cross-spectral approach. Finance Research Letters.
  25. [18] Shunrong Shen, Haomiao Jiang, and Tongda Zhang. Stock market forecasting using machine learning algorithms. Stanford University, 2012.
  26. [19] Jan Ivar Larsen. Predicting stock prices using technical analysis and machine learning. NTNU, 2010.
  27. [20] Vatsal H. Shah. Machine learning techniques for stock prediction. NYU, 2007.
  28. [21] JF Andru, Fabio Mangatas Silaen, Hendy Tannady, Kevin Hadi Saputra. Electronic health record to predict a heart attack used data mining with Naïve Bayes
  29. method. International Journal of Informatics and Communication Technology (IJ-ICT). 2021
  30. [22] Felliks Feiter Tampinongkol, Yudi Setiawan, dll. Canopy Cover Estimation Based on LiDAR and Landsat 8 Data using Support Vector Regression.
  31. International Conference on Data and Software Engineering (ICoDSE). 2021
  32. [23] JF Andry, H. Tannady. Big Data Analysis On Youtube with Tableau. Journal of Theoritical and Applied Information Technology. 2021
  33. [24] JF Andry, J Gunadi GD Rembulan. Big Data Implementation in Tesla using Classification with Rapid Miner. The International Journal of Nonlinear Analysis
  34. and Application (IJNAA). 2021
  35. [25] ED Madyatmadja, M. Marvell, JF Andry, H. Tannady, A Chakir. Implementation of Big Data in Hospital using Cluster Analytics. International Conference
  36. on Information Management and Technology (ICIMTech)
  37. [26] JF Andry, H. Hartono, AC Honni. Data Set Analysis Using Rapid Miner to Predict Cost Insurance Forecast with Data Mining Methods. Journal of Hunan
  38. University Natural Science