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This is a Quantitative Study study.

Social Media X-Based Public Opinion Analysis of Prabowo-Gibran Government's First 100 Days Using Naïve Bayes and K-Nearest Neighbor Classification Methods

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Sentiment analysis reveals negative public perception of Prabowo-Gibran government in 431 tweets, suggesting improvements are needed.

Public sentiment analysis showed 62% negativity in the first 100 days of the Prabowo-Gibran administration.
Naïve Bayes achieved 97.22% accuracy in sentiment classification versus KNN's 62.65% performance.
Approach utilized machine learning techniques, focusing on text data from social media.
Findings signal the need for enhanced models to interpret sarcasm and nuanced expressions in future analyses.

Afifah et al. (2025) studied this question.

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