Analisis Sentimen Masyarakat terhadap Kebijakan Vaksinasi Covid-19 di Indonesia pada Twitter Menggunakan Algoritma LSTM

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Published: Dec 31, 2022
DOI: https://doi.org/10.17933/iptekkom.24.2.2022.161-172
Keywords:
Covid-19, LSTM (Long Short-Term Memory), Sentiment Analysis, Twitter, Vaccination
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Laila Marifatul Azizah
Universitas Muhammadiyah Yogyakarta
Dimas Bagas Ajipratama
Universitas Muhammadiyah Yogyakarta
Nisrina Akbar Rizky Putri
Cahya Damarjati
Universitas Muhammadiyah Yogyakarta

Abstract

Indonesia was shocked by the emergence of the first case of Covid-19 in March 2020. The Covid-19 virus can be fought with herd immunity, namely by vaccinating. On December 16, 2020, President Joko Widodo announced that he would provide the Covid-19 vaccine to the people of Indonesia. The information received various responses from the public. One of them through twitter. There are opinions that support and there are also those who reject vaccination. To find out the opinion of public sentiment regarding vaccination, a sentiment analysis process is carried out using an algorithm that aims to assist the sentiment analysis process with quite a lot of data. In this study, the sentiment analysis process uses one of the deep learning methods, namely LSTM (Long Short-Term Memory). The results of this study tend to support the vaccination program by producing 79% positive tweets, 13% neutral tweets and 8% negative tweets and getting a model accuracy of 71% using parameters of 15 epochs, 64 batch sizes and a comparison of training data and test data of 9:1 ​​(3600:400).

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Vol. 24 No. 2 (2022): Jurnal IPTEK-KOM (Jurnal Ilmu Pengetahuan dan Teknologi Komunikasi)
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