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

arXiv: https://arxiv.org/abs/2604.26312 · HTML: https://mlsanity.com/paper/2604.26312/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
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- First posted on arXiv 29 Apr 2026.

## Abstract (arXiv)

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