Sentiment Analysis Of The Indonesian National Team'S Erspo Jersey

This study analyzes public sentiment towards the new jersey design of the Indonesian National Team (Timnas) using the Naive Bayes classification method on the Twitter platform. The background of the study is fan dissatisfaction with the jersey design that does not meet expectations, as well as the designer who does not accept criticism or input from various parties. Data was taken through a crawling process from Twitter using the keyword "timnas Indonesia," resulting in 1229 tweets categorized as positive, negative, or neutral. The preprocessing process includes cleansing, case folding, tokenization, stopword removal, stemming, and TF-IDF. After preprocessing, the data is labeled with sentiment. The classification results using Naive Bayes show an accuracy of 99%, precision and recall reaching a maximum value of 1.00 for most classes, with an F1-score of 1.00 for classes 1 and 2, and 0.98 for class 2 with most tweets having neutral sentiment, followed by positive and negative sentiment. Data visualization through word clouds and bar graphs shows the main topics discussed regarding the jersey, such as "jersey," "timnas," "Indonesia," "price," and "buy." This study concluded that the Erspo Indonesian National Team jersey was generally well-received in the online community, with a majority of the sentiment being neutral and a small portion being positive. This indicates that although the majority of responses were neutral, the jersey still did not generate significant negative sentiment, so it was considered well-received overall. The Naive Bayes model proved effective in classifying sentiment from tweets, providing valuable insights for improving products and services related to the Indonesian National Team jersey.