Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
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This Author published in this journals
All Journal Indonesian Journal on Computing (Indo-JC) AT-TAKLIM: Jurnal Pendidikan Multidisiplin
Muhammad Rahman Ali
Unknown Affiliation
Computer Science & IT Other

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Journal : Indonesian Journal on Computing (Indo-JC)

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Public Perception of Buying and Selling Bitcoin Using Lexicon Sentiment Analysis Muhammad Rahman Ali; Wijaya, Rifki; Yunanto, Prasti Eko
Indonesia Journal on Computing (Indo-JC) Vol. 9 No. 2 (2024): August, 2024
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2024.9.2.980

Abstract

This study investigates public perceptions of Bitcoin (BTC) trading using sentiment lexicon analysis. The rapid growth of cryptocurrency trading has attracted significant public interest and investment, making it crucial to understand the sentiments and opinions surrounding BTC transactions. By employing sentiment lexicon methods, this research analyzes tweets and social media posts to determine public sentiment. The study aims to identify trends and patterns in public opinion, providing insights into how sentiment impacts BTC trading behavior. Preliminary results indicate a correlation between positive sentiment and increased trading activity, while negative sentiment correlates with market declines. This research contributes to a better understanding of the role of public sentiment in the volatile cryptocurrency market.
Public Perception of Buying and Selling Bitcoin Using Lexicon Sentiment Analysis Muhammad Rahman Ali; Wijaya, Rifki; Yunanto, Prasti Eko
Indonesian Journal on Computing (Indo-JC) Vol. 9 No. 2 (2024): August, 2024
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2024.9.2.980

Abstract

This study investigates public perceptions of Bitcoin (BTC) trading using sentiment lexicon analysis. The rapid growth of cryptocurrency trading has attracted significant public interest and investment, making it crucial to understand the sentiments and opinions surrounding BTC transactions. By employing sentiment lexicon methods, this research analyzes tweets and social media posts to determine public sentiment. The study aims to identify trends and patterns in public opinion, providing insights into how sentiment impacts BTC trading behavior. Preliminary results indicate a correlation between positive sentiment and increased trading activity, while negative sentiment correlates with market declines. This research contributes to a better understanding of the role of public sentiment in the volatile cryptocurrency market.
Co-Authors Prasti Eko Yunanto Rifki Wijaya