Analisis Sentimen Menggunakan Metode Naive Bayes Pada Komentar Penonton YouTube Windah Basudara - Adam Putra Berlin; Arafat Febriandirza (Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika), 2025)
The development of social media has provided users with a space to express their opinions through comments, including on the YouTube platform. One content creator who has a large fanbase and active comment section is Windah Basudara. This study aims to analyze the sentiment of viewer comments on one of Windah Basudara’s videos using the Naive Bayes algorithm. This method was chosen due to its effectiveness in text classification and sentiment analysis. The data used consists of comments from the video titled "Mencoba NAMATIN game Keju Joget", which were collected randomly and cleaned through text preprocessing steps such as case folding, tokenizing, stopword removal, and stemming. The comments were classified into two sentiment categories: positive and negative. The analysis results show that the majority of comments carry a positive sentiment, reflecting a favorable response from viewers toward the presented content. The model evaluation demonstrates satisfactory classification results. This study is expected to contribute to understanding audience perception of YouTube content and serve as a reference for further analysis on social media platforms.