<![CDATA[Public opinion expressed on social media increasingly mirrors consumer perception of brands in the Fast-Moving Consumer Goods (FMCG) sector. This study builds and compares sentiment analysis models to objectively classify public opinion toward three Danone Indonesia brands, namely AQUA, Mizone, and SGM, based on conversations on X/Twitter, while identifying the topics that shape that opinion. Data were collected legally through the official X/Twitter API v2, yielding 5,813 Indonesian-language tweets posted between May 2025 and June 2026 after duplicate removal. Three annotators labeled relevance and sentiment, with reliability assessed using Fleiss' Kappa, and the text was represented through TF-IDF weighting. Four classifiers, namely Naive Bayes, Support Vector Machine (SVM), Decision Tree, and Logistic Regression, were compared using cross validation, while Latent Dirichlet Allocation modeled the topics. After hyperparameter tuning and stratified ten-fold validation, SVM was the most accurate and stable model, reaching 88.80% accuracy and 88.19% macro F1. AQUA was dominated by negative opinion driven by a water-source controversy, whereas Mizone and SGM leaned positive. Integrating sentiment analysis and topic modeling objectively measures and explains public opinion toward FMCG brands.]]>
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