Analisis Sentimen Masyarakat Terhadap Kondisi Jalan Rusak Batu Jomba Menggunakan Algoritma Naive Bayes
DOI:
https://doi.org/10.71242/jz9zsh33Keywords:
Sentiment Analysis, Damaged Road Conditions, Naive Bayes, YouTubeAbstract
The condition of the damaged Batu Jomba road has become a serious concern for the wider community. To understand public sentiment regarding the condition of the road, this research uses sentiment analysis with the Naive Bayes algorithm. This study aims to analyze public sentiment regarding the damaged road conditions of Batu Jomba on the YouTube channel @bayobuan using the Naive Bayes algorithm. The data used consists of comments on videos related to the condition of the Batu Jomba road, totaling 500 comments. The data was then processed using data preprocessing techniques, including tokenization, stopword removal, and lemmatization. The analysis results show that public sentiment towards the condition of Batu Jomba road is negative, with a negative sentiment percentage of 75%. Positive sentiment only reaches 15%, while neutral sentiment is 10%. The Naive Bayes algorithm can classify sentiment with an accuracy of 90%, a precision of 85%, and a recall of 95%. The results of this study can be used as a reference for improving the condition of Batu Jomba road and enhancing the quality of public services. In addition, the results.
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