<![CDATA[The change in the coach of the Indonesian national team has ignited a range of public responses on social media, particularly on the X platform (formerly Twitter). This research intends to examine public opinion regarding the firing of coach Shin Tae-yong and the hiring of Patrick Kluivert through the Support Vector Machine (SVM) algorithm. A dataset of 1,000 public comments was gathered via crawling methods from the @timnasindonesia account, subsequently classified as either positive or negative sentiment using a lexicon-based technique. The stages of the research involved text preprocessing (cleaning, tokenization, stemming, and stopword elimination), word weighting through TF-IDF, and sentiment classification with the SVM algorithm. Initial findings indicated a classification accuracy of 77%, which rose to 83% following upsampling to rectify class imbalance. The evaluation of the model utilized a confusion matrix, resulting in high precision, recall, and F1-score metrics. This research shows that SVM is successful in categorizing public sentiment on particular social matters and can serve as a data-informed decision-making resource. These findings further enhance understanding of public views on strategic policies within national sports, especially football.]]>
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