TEXT CLASSIFICATION OF TWITTER OPINION RELATED TO PERMENDIKBUD 30/2021 USING BIDIRECTIONAL LSTM

  • Zakiyatul Fitriyah Department of Statistics, Universitas Islam Indonesia, Indonesia
  • Mujiati Dwi Kartikasari Department of Statistics, Universitas Islam Indonesia, Indonesia
DOI: https://doi.org/10.30598/barekengvol17iss2pp1113-1122
Keywords: Permendikbud 30/2021, Classification, LSTM, BiLSTM

Abstract

During the COVID-19 outbreak, sexual violence in Indonesia has risen. Sexual abuse is prevalent even within the realm of education. Many incidents of sexual assault are reported within the higher education sector. The Ministry of Education, Culture, Research, and Technology published Decree of the Minister of Education and Culture Number 30/2021 (Permendikbud 30/2021) on the Prevention and Handling of Sexual Violence in Higher Education in an effort to prevent sexual violence on campus. This regulation's issuance has become a popular topic of discussion on social media. Twitter is one of the social media platforms where opinions are expressed. The publication of Permendikbud 30/2021 elicited a variety of views, from those who supported the rule to those who did not. This study's objective is to categorize tweets about Permendikbud 30/2021. Bidirectional LSTM (BiLSTM) was utilized to classify data in this study. The accuracy values are 87%, the precision values are 82%, and the recall values are 96% based on the findings of the analysis comparing training data of 80% to testing data of 20%.

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Published
2023-06-11
How to Cite
[1]
Z. Fitriyah and M. Kartikasari, “TEXT CLASSIFICATION OF TWITTER OPINION RELATED TO PERMENDIKBUD 30/2021 USING BIDIRECTIONAL LSTM”, BAREKENG: J. Math. & App., vol. 17, no. 2, pp. 1113-1122, Jun. 2023.
Issue
Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Section
Articles

Copyright (c) 2023 Zakiyatul Fitriyah, Mujiati Dwi Kartikasari

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