Analysis of Public Opinion on TikTok Regarding the MBG Program Controversy Using the Support Vector Machine Algorithm
-
Fera Febrianti
*
Universitas Muhammadiyah Bima, Bima,
Indonesia
- Sahrul Ramadhan Universitas Muhammadiyah Bima, Bima, Indonesia
- Irfan Irfan Universitas Muhammadiyah Bima, Bima, Indonesia (*) Corresponding Author
Abstract
This study examines the analysis of public opinion regarding the controversy surrounding the Free Nutritional Meal Program (MBG), a strategic policy of the Indonesian government aimed at reducing stunting rates and improving child nutrition. Despite its important social objectives, the program has sparked various public reactions concerning budget transparency, equitable distribution of aid, and food security. TikTok, as a social media platform with high levels of interaction, has become a primary platform for the public to express opinions on public policy. However, its use in sentiment analysis research remains relatively limited compared to other platforms such as Twitter and Instagram. This study aims to analyze public perceptions of the MBG program using a combination of the Support Vector Machine (SVM) algorithm and Word2vec. Research data was obtained through the collection of 2,381 TikTok comments, followed by preprocessing steps such as data cleaning, tokenization, slang normalization, stop-word removal, and stemming. After the data selection process, 2,376 comments were used in the lexicon-based sentiment labeling and classification process using SVM. The test results show that the SVM model achieved an accuracy of 80% before class imbalance handling, whereas after applying class imbalance handling techniques, the accuracy increased to 83%, with a weighted precision of 0.84, a recall of 0.83, and an F1 score of 0.83. This improvement indicates that processing the data in the database enhances the model’s ability to recognize all sentiment classes more evenly, particularly positive sentiment, which previously had a smaller dataset. The sentiment analysis results show that the majority of opinions are dominated by neutral and negative sentiments, reflecting public concerns regarding the program’s implementation effectiveness, budget management transparency, and equitable distribution. These findings suggest that public opinion on social media can be leveraged as a real-time source for evaluating government policies to help the government develop public communication strategies that are more transparent, responsive, and targeted toward the implementation of the MBG Program.
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