Penerapan Ontology Berbasis Protégé Untuk Mengestimasi Nilai Ekonomi Cryptocurrency

Authors

  • Muhammad Ashardiansyah Putra Universitas Bina Darma
  • Ferdiansyah Ferdiansyah Universitas Bina Darma
  • Linda Atika Universitas Bina Darma
  • Kiky Rizky Nova Wardani Universitas Bina Darma

DOI:

https://doi.org/10.51519/journalita.volume2.isssue2.year2021.page77-89

Keywords:

ABSTRACT Cryptoccurency is a digital currency that is used as a medium of exchange as well as rupiah and dollars. And just like currency, Cryptocurrency also experiences value volatility or commonly reffered to as fluctuation. The purpose of this study is to estimate the fluctuating cryptocurrency value by implementing it into ontology using protégé tools. With the ontology, it can make it easier for users to find information about cryptocurrency. The results of this study indicate that ontology is one of the bases of Knowledge Managament Systems which can make it easier to systematizem, improve and accelerate knowledge management so that it is easy to understand for cryptocurrency users. Another result of this research is the creation of an ontology cryptoccurency with the blockchain subclass, users, currency, economu and factors. Each of these subclasses has more subclasses in a structured manner, and the results of making computer technique ontology in estimating the economic value of cryptocurrency are useful for users or people who want to find out more information about cryptocurrency. Keywords : cryptocurrency, ontology, Knowledge Management System, protégé

Abstract

Cryptoccurency is a digital currency that is used as a medium of exchange as well as rupiah and dollars. And just like currency, Cryptocurrency also experiences value volatility or commonly reffered to as fluctuation. The purpose of this study is to estimate the fluctuating cryptocurrency value by implementing it into ontology using protégé tools. With the ontology, it can make it easier for users to find information about cryptocurrency. The results of this study indicate that ontology is one of the bases of Knowledge Managament Systems which can make it easier to systematizem, improve and accelerate knowledge management so that it is easy to understand for cryptocurrency users. Another result of this research is the creation of an ontology cryptoccurency with the blockchain subclass, users, currency, economu and factors. Each of these subclasses has more subclasses in a structured manner, and the results of making computer technique ontology in estimating the economic value of cryptocurrency are useful for users or people who want to find out more information about cryptocurrency.

References

F. Mulyanto, “Pemanfaatan Cryptocurrency Sebagai Penerapan Mata Uang Rupiah Kedalam Bentuk Digital Menggunakan Teknologi Bitcoin,” IJNS--Indonesian J. Netw. Secur., vol. 4, no. 4–2015, 2015.

K. Wu, S. Wheatley, and D. Sornette, “Classification of cryptocurrency coins and tokens by the dynamics of their market capitalizations,” R. Soc. open Sci., vol. 5, no. 9, p. 180381, 2018.

N. O. Syamsiah, “Kajian atas cryptocurrency sebagai alat pembayaran di Indonesia.”

Y. Ki, E. Kim, and H. K. Kim, “A novel approach to detect malware based on API call sequence analysis,” Int. J. Distrib. Sens. Networks, vol. 2015, 2015.

T. A. O. FENG, J.-Y. TANG, and J.-Z. LIAO, “Ontology Construction for Domain of Digital Money,” DEStech Trans. Eng. Technol. Res., no. pmsms, 2018.

S. Kim, A. Sarin, and D. Virdi, “Crypto-assets unencrypted,” J. Invest. Manag. Forthcom., 2018.

F. Ferdiansyah, S. H. Othman, R. Z. R. M. Radzi, D. Stiawan, Y. Sazaki, and U. Ependi, “A LSTM-Method for Bitcoin Price Prediction: A Case Study Yahoo Finance Stock Market,” in 2019 International Conference on Electrical Engineering and Computer Science (ICECOS), 2019, pp. 206–210.

K. K. Lane, Domains as Community Structure within Ontologies: Towards a Macro-Structure Model of Knowledge. University of California, Los Angeles, 2011.

Ferdiansyah et al., “Analysis and forecasting of Time-Series data using S-ARIMA, CNN and LSTM,” Telkomnika (Telecommunication Comput. Electron. Control., vol. 19, no. 3, pp. 206–210, 2021.

D. R. Pant, P. Neupane, A. Poudel, A. K. Pokhrel, and B. K. Lama, “Recurrent Neural Network Based Bitcoin Price Prediction by Twitter Sentiment Analysis,” in 2018 IEEE 3rd International Conference on Computing, Communication and Security (ICCCS), 2018, pp. 128–132.

S. McNally, J. Roche, and S. Caton, “Predicting the price of Bitcoin using Machine Learning,” in Parallel, Distributed and Network-based Processing (PDP), 2018 26th Euromicro International Conference on, 2018, pp. 339–343.

F. Ferdiansyah, E. S. Negara, and Y. Widyanti, “BITCOIN-USD trading using SVM to detect the current day’s trend in the market,” J. Inf. Syst. Informatics, vol. 1, no. 1, pp. 70–76, 2019.

A. Radityo, Q. Munajat, and I. Budi, “Prediction of Bitcoin exchange rate to American dollar using artificial neural network methods,” in Advanced Computer Science and Information Systems (ICACSIS), 2017 International Conference on, 2017, pp. 433–438.

A. Greaves and B. Au, “Using the bitcoin transaction graph to predict the price of bitcoin,” No Data, 2015.

M. W. P. Aldi, J. Jondri, and A. Aditsania, “Analisis Dan Implementasi Long Short Term Memory Neural Network Untuk Prediksi Harga Bitcoin,” eProceedings Eng., vol. 5, no. 2, 2018.

Downloads

Published

2021-08-09

How to Cite

Putra, M. A., Ferdiansyah, F., Atika, L., & Wardani, K. R. N. (2021). Penerapan Ontology Berbasis Protégé Untuk Mengestimasi Nilai Ekonomi Cryptocurrency. Journal of Information Technology Ampera, 2(2), 77–89. https://doi.org/10.51519/journalita.volume2.isssue2.year2021.page77-89