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Indonesian Society’s Sentiment Analysis Against the COVID-19 Booster Vaccine

Authors :
Dionisia Bhisetya Rarasati
Angelina Pramana Thenata
Afiyah Salsabila Arief
Source :
Jurnal Nasional Teknik Elektro dan Teknologi Informasi, Vol 12, Iss 4, Pp 274-279 (2023)
Publication Year :
2023
Publisher :
Universitas Gadjah Mada, 2023.

Abstract

The COVID-19 pandemic is still occurring in various countries, including Indonesia. This pandemic is caused by the coronavirus, which has mutated into multiple virus variants, such as Delta and Omicron. As of 9 February 2022, 4,626,936 people were confirmed positive for COVID-19 in Indonesia. This number continues to rise. The Indonesian government has prevented the spread of these virus variants by introducing booster vaccines to the public. However, this vaccination program has caused various sentiments among Indonesians. To optimize efforts to combat COVID-19, the government needs to know these sentiments immediately. Based on these problems, the researcher proposes the application of machine learning technology to develop a system that can analyze the sentiments of the Indonesians toward the booster vaccine. This research has several stages: data collection, data labeling, text preprocessing, feature extraction, and application of the support vector machine (SVM) algorithm using various kernels, namely the linear kernel, Gaussian radial basis function (RBF) kernel, and polynomial kernel. Furthermore, the results of the system were tested for accuracy using a 10-fold cross validation and confusion matrix. The dataset used was 681 tweets with the hashtag “vaksinbooster.” The dataset consists of two classes: negative (0) and positive (1). The results showed that the data were positive for the booster vaccine, as evidenced by the higher number of positive tweets, with 554 data, compared to 127 negative tweets. In addition, the dataset was divided into training data of 545 and testing data of 136. In addition, the test results of this study revealed that the SVM algorithm with the polynomial kernel, which was evaluated with 10-fold cross validation, yielded the highest level of accuracy, namely 79.22%.

Details

Language :
English, Indonesian
ISSN :
23014156 and 24605719
Volume :
12
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Publication Type :
Academic Journal
Accession number :
edsdoj.bf5e29e3fed436d926f4d34b9731f5f
Document Type :
article
Full Text :
https://doi.org/10.22146/jnteti.v12i4.5125