Sentiment Analysis of Delivery Services Using the Sastrawi Library and Biobii Naive Bayes Text Classifier

Abstrak

Sentiment analysis from social media is an important aspect to find out people's views. This research produces a web-based system that can analyze public sentiment towards a delivery service based on social media Twitter (currently X). The technology used is the Twitter(X) API, Sastrawi library and Biobii Naïve Bayes text classifier. The Twitter(X) API is used to retrieve data from the Twitter(X) social media platform, while the Sastrawi library is used to process and analyze texts in Indonesian. In this system users can enter certain keywords or hashtags for analysis. The collected tweet data is then processed using a customized Naïve Bayes text classifier Library to identify positive and negative sentiments towards the services offered by a delivery service company. The results of sentiment analysis are displayed in the form of informative graphical visualizations, providing a better understanding of customer views regarding the service. The accuracy of the sentiment analysis results produced was based on testing with one of the delivery service companies, obtaining results with a value of 93.75% accurate.

Identifier

• DOI: https://doi.org/10.67758/appissode.v4i2.55
• OpenAlex: https://openalex.org/W7201953180