Sentiment Analysis of Indonesian National Team Football Match Results in the U-23 Asian Cup on the YouTube Platform using the Support Vector Machine (SVM) Algorithm
https://doi.org/10.58466/aicoms.v3i1.1528
Keywords:
Analisis Sentimen, Support Vector Machine (SVM), Tim Nasional Indonesia, Piala Asia U23Abstract
This study aims to analyze YouTube users' perceptions of the Indonesian national football team's matches in the 2024 AFC U23 Asian Cup. The research seeks to identify whether user sentiments toward the team's match results are positive, negative, or neutral. By using comments from the YouTube platform, the study examines public reactions to the outcomes of the Indonesian national team's matches in the U23 Asian Cup. Sentiment analysis of the match results was conducted using the Support Vector Machine (SVM) algorithm. Two SVM-based classification models were evaluated, one utilizing 40% of the data for testing and the other using 60%.
The findings reveal that the first model, with 40% test data, achieved an accuracy of 65.41%, while the second model achieved an accuracy of 63.76%. Although the first model demonstrated slightly higher accuracy, the second model performed better in terms of precision (61.65%), recall (63.76%), and F1-Score (55.68%).
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