Article Per Year (5 Year)
p-Index From 2020 - 2025
1.642
P-Index
This Author published in this journals
All Journal Jurnal Promosi Pendidikan Ekonomi Jurnal Proyek Teknik Sipil Brilliance: Research of Artificial Intelligence Informatics and Enginering Dedication Journal of Management and Digital Business Publikasi Riset Mahasiswa Manajemen Journal of Mutidisciplinary Issues MDP Student Conference International Journal of Application on Economics and Business
Nicholas, Nicholas
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Social Sciences Other

Published : 10 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Journal of Mutidisciplinary Issues

 1 
Sentiment Analysis Comparative Analysis of Sentiment Analysis Using the Support Vector Machine and Naive Bayes Algorithm on Cryptocurrencies: CRISP - DM Nicholas, Nicholas; Sutomo, Rudi
Journal of Multidisciplinary Issues Vol 1 No 3 (2021): Journal of Multidisciplinary Issues
Publisher : APPS Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1098.281 KB) | DOI: 10.53748/jmis.v1i3.22

Abstract

Objective – Cryptocurrency is growing overtime even being adopted as a legal money in a country out there. Besides can be used as a money, cryptocurrency also can be used as a digital goods to be trade and investment assets. To do some investing in cryptocurrency, there’s a need to evaluate the fundamental and sentiment of that cryptocurrency. This study aims to evaluate cryptocurrency based on responses of Twitter user.Methodology – The Algorithms used in this sentiment analysis study are Support Vector Machine and Naïve Bayes because it’s already proven that these 2 algorithm able to give a good accuracy and performance and using CRISP – DM framework for the study flow.Findings – This research predicts the sentiment for Bitcoin, Ethereum, Binance Coin, Dogecoin, and Ripple using the CRISP - DM method and using Support Vector Machine and Naïve Bayes algorithm.Novelty – This study calculate the sentiment on cryptocurrency using Rapidminer tools.Limitations - This study uses Bitcoin, Ethereum, Binance Coin, Dogecoin, and Ripple using tools such as rapidminerKeywords — Cryptocurrency, Naïve Bayes, Sentiment Analysis, Support Vector Machine
Co-Authors Anjang Nugroho, Anjang Ariyanto, Hepy Hefri Butarbutar, Hotni Mutiara Candra candra Chandra, Kelvin William Ekadjaja, Margarita Elizabeth, Sri Megawati Hartati, Ery Larissa, Jesslyn Liu, Lisa Carline M Ezar Al Rivan Putra Darmansius, Albertus Dwi Andhika Putra, Edy Yulianto Qadri, Rizni Aulia Sasongko, Randie Susanti, Oktris Sutomo, Rudi Yang, Jenny Yuki, Narumi