Analisis Sentimen Pada Media Sosial Instagram Terhadap Akun Presiden Joko Widodo Menggunakan Metode Naïve Bayes Classifier
DOI:
https://doi.org/10.54066/jptis.v2i2.1895Keywords:
Accuracy, Instagram, Jokowi, Naïve Bayes Classifier, Sentiment AnalysisAbstract
In the growing digital era, social media, especially Instagram, has become the main platform for people to communicate and express themselves. One of the most influential accounts is President Joko Widodo's official account, @jokowi, which is often in the spotlight with thousands of comments covering a wide range of sentiments, both positive and negative. In the midst of his popularity, sentiment analysis is key to understanding the public's views on Jokowi's leadership. This study aims to analyze public sentiment towards President Joko Widodo (Jokowi) through comments posted on his official Instagram account (@jokowi). By utilizing the Naïve Bayes Classifier method, this study collected data from 1000 comments which were then processed through various stages of the methodology, including data collection, preprocessing, weighting, k-fold cross validation, and method implementation. Through the preprocessing stage involving cleansing, stopword removal, stemming, and tokenizing, the comments were prepared for further analysis. Test results using k-fold cross validation show that the model has an average accuracy of 80.3%. In addition, evaluation using confusion matrix showed an accuracy of 84.1%, with a precision of 85.5% and recall of 92.4%. These results show that the Naïve Bayes Classifier method performs well in classifying positive and negative sentiments in the comments.
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