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Journal of Mutidisciplinary Issues
Published by APPS Publications
ISSN : -     EISSN : 27986454     DOI : https://doi.org/10.53748/jmis.v1i1
Core Subject : Science, Agriculture, Social, Engineering,
Agriculture, Biological Sciences & Forestry Computer Science & IT Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science
Journal of Multidisciplinary (JMIS), Focus and Scope is Information Technology, Psychology, Environmental Science, Data Science, Language and Linguistics, Education, Data Sensor and Networking, Information System, Gamification, Health Science. JMIS is published frequency quarterly (May, August, November, and February) by APPS Publications.` This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge. Every manuscript submitted to JMIS will not have any Article Processing Charges and Article Submission Charges. This includes submitting, peer-reviewing, editing, publishing, maintaining and archiving, and allows immediate access to the full-text versions of the articles.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 1 Documents
 1 
Search results for , issue "Vol 1 No 3 (2021): Journal of Multidisciplinary Issues" : 1 Documents clear
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

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