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arXiv · 2604.26312

Classification of Public Opinion on the Free Nutritional Meal Program on YouTube Media Using the LSTM Method

Berliana Enda Putri·Lisa Diani Amelia·Muhammad Zaky Zaiddan·Luluk Muthoharoh·Ardika Satria·Martin Clinton Tosima Manullang
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Abstract

Public opinion towards the Free Nutritious Meal Program (MBG) on YouTube social media reflects diverse community responses. This study applies the Long Short-Term Memory (LSTM) method to classify sentiments from 7,733 YouTube comments. The results show that the LSTM model achieves 89% accuracy, with strong performance on negative sentiment (F1-score 0.94) but weaker performance on positive sentiment (F1-score 0.55) due to class imbalance, as negative data account for 87.7% of the dataset. These findings confirm the effectiveness of LSTM for sentiment analysis of Indonesian text while highlighting the challenge of imbalanced data. This research contributes to social media-based public policy evaluation

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Berliana Enda Putri, Lisa Diani Amelia, Muhammad Zaky Zaiddan, Luluk Muthoharoh, Ardika Satria, Martin Clinton Tosima Manullang. 2026-04-29. Classification of Public Opinion on the Free Nutritional Meal Program on YouTube Media Using the LSTM Method. https://arxiv.org/abs/2604.26312

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