Sentiment Analysis of Youtube and Gotube Reviews on Google Play Using the Support Vector Machine (SVM) Method in Indonesia
DOI:
https://doi.org/10.30871/jaic.v9i3.9461Keywords:
Sentiment Analysis, Support Vector Machine (SVM), Google Play Reviews, Youtube, GotubeAbstract
This research, titled Sentiment Analysis of YouTube and GoTube Reviews on Google Play Using the Support Vector Machine (SVM) Method in Indonesia, analyzes user perceptions of YouTube and GoTube based on Google Play reviews. The study is motivated by the growing popularity of video streaming apps in Indonesia and the limited sentiment analysis research on these platforms. The research collects 1,600 reviews (800 per app) from 2023-2024 using Python’s Scrapy library. The data is split 70% for training and 30% for testing, undergoing text preprocessing (tokenization, stop word removal, stemming), TF-IDF weighting, and SVM classification with an RBF kernel. Evaluation metrics include accuracy, precision, recall, and F1-score, with PCA used for visualization. Results show 94.50% accuracy overall, 97.01% for YouTube, and 92.66% for GoTube. GoTube has higher positive sentiment (385 of 400 test reviews) than YouTube (345 of 400) but lower negative sentiment (15 vs. 55). However, the model exhibits a positive class bias due to data imbalance. The study concludes that SVM effectively detects positive sentiment, but balancing data and exploring non-linear methods could improve negative sentiment detection.
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