Public Sentiment Analysis Against Tokocrypto Exchange on Twitter Using LSTM Method

Authors

  • Green Arther Sandag Universitas Klabat
  • Jacquline Waworundeng Universitas Klabat

DOI:

https://doi.org/10.31154/cogito.v8i2.418.411-421

Keywords:

Internet, Cryptocurrency, Investment, Exchange, Tokocrypto, LSTM

Abstract

The internet has played an important role in influencing all human activities in today's technological era. With the internet can be used for various purposes, including sharing knowledge, transacting, socializing, shopping, business, education, and many other things that can be done. While the internet is getting more and more popular, various kinds of digital transactions continue to develop, one of which is the exchange of coins for other coins which are called cryptocurrencies. Cryptocurrencies are digital assets that use strong cryptography to encrypt financial transactions, and verify asset transfers. One of the cryptocurrency exchanges for investment in Indonesia is Tokocrypto. With such enthusiasm for cryptocurrency, many Indonesians use social media such as Twitter to find information, provide opinions, as well as information. To classify public tweets on Twitter into positive and negative categories, a sentiment analysis model is needed. This study uses the Long Short Term Memory (LSTM) method, where LSTM is a neural network development that can be used for modeling time series data on Twitter users' tweets against the Tokocrypto exchange. There were 2022 positive tweets, 1632 negative tweets, and 1012 neutral tweets.

Author Biography

Green Arther Sandag, Universitas Klabat

Program Studi Teknik Informatika

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Cogito Vol.8 No.2 - December 2022

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Published

2022-12-27

How to Cite

Sandag, G. A., & Waworundeng, J. (2022). Public Sentiment Analysis Against Tokocrypto Exchange on Twitter Using LSTM Method. CogITo Smart Journal, 8(2), 411–421. https://doi.org/10.31154/cogito.v8i2.418.411-421

Issue

Vol. 8 No. 2 (2022): Cogito Smart Journal

Section

Articles

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