Analisis Sentimen Masyarakat Terhadap Liga Indonesia Menggunakan Algoritma Naïve Bayes Classifier dan Support Vertor Machine Pada Platform X dan YouTube
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Mahyuda Irwanda
*
Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru,
Indonesia
- M Afdal Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia
- Rice Novita Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia
- Zarnelly Zarnelly Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia (*) Corresponding Author
Abstract
The Indonesian League is a national football competition that attracts a lot of public attention. However, various problems such as controversial referee decisions, fan riots, and match-fixing issues are often in the spotlight. This study aims to analyze public sentiment towards the Indonesian League using the Naïve Bayes Classifier (NBC) and Support Vector Machine (SVM) algorithms. Data were collected from social media platform X (Twitter) as many as 2000 tweets and YouTube as many as 2000 comments in the period from January 2023 to December 2024. After going through preprocessing stages such as cleaning, case folding, tokenizing, stopword removal, and stemming, the data was classified into positive, negative, and neutral sentiments. The results showed that SVM had a higher accuracy (99%) than NBC (85%) in sentiment analysis.
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