Analisis Sentiment Cyberbullying pada media Youtube menggunakan Algoritma NaÃ¯ve Bayes - Elfansyah, Muhammad Rayhan; Perdana, Muhammad Reifin; Ihram Nabawi, Ikhsan Nuttakwa Takbirata; Rudiman, Rudiman (Universitas Muhammadiyah Ponorogo, 2024)
This research focuses on analyzing cyberbullying sentiment on YouTube using the Naive Bayes algorithm. This study involved data collection and data pre-processing techniques to analyze comments related to Manchester United. The Orange Data Mining application is used for data modeling and analysis. The research methodology and sentiment analysis using Naive Bayes are explained in detail. Data pre-processing includes steps such as removing URLs, tokenization, filtering, and normalization. Analysis uses NaÃ¯ve Bayes which produces 81% accuracy, 79% precision and 81% recall. The process includes dividing the data into training data and testing data, and the results can be visualized using a confusion matrix. The references include various studies on sentiment analysis using different methods and platforms.