Analisis Sentimen Program Makan Gratis Pada Media Sosial X Menggunakan Metode NLP - Anggriyani, Wisda; Fakhriza, Muhammad (Journal of Computer System and Informatics (JoSYC), 2024)
This study aims to analyze public sentiment toward the free meal program initiated on Social Media X. Utilizing Natural Language Processing (NLP) methods klasification navie bayes, this research processes text data collected from various user comments and posts on the platform. The collected data is then classified into positive, negative, and neutral sentiment categories. The analysis process involves text preprocessing techniques, including tokenization, stemming, and stop words removal, to enhance the accuracy of the sentiment model. The analysis results show that most users responded positively to the program, particularly regarding the social benefits it offers. However, some negative sentiments were also detected, primarily related to the program's implementation and the quality of the provided meals. These findings offer valuable insights for program organizers to comprehensively understand public perception and make improvements in the future. This study also highlights the importance of using NLP in social media data analysis as a tool to identify and understand public opinion on a large scale.