Analisis Sentimen Masyarakat Terhadap Generasi Z Dalam Dunia Kerja Pada Media Sosial Twitter Menggunakan Metode Naïve Bayes

Generation Z, born between 1996 and 2010, is now entering the workforce
and is known as "Digital Natives" due to their familiarity with technology and
social media such as Twitter. They are actively sharing thoughts and experiences
through Twitter, which has become the primary platform for open discussion and
sharing perspectives. This research employs the Naïve Bayes method to analyze
sentiment in tweets related to Generation Z in the workplace, utilizing the Inset
lexicon labeling.The results indicate that the Inset lexicon labeling achieved an
accuracy of 76%. Furthermore, experiments with manual labeling yielded an
accuracy of 87%, demonstrating a significant difference compared to the lexicon�based approach. The study also examined the influence of stopwords during
preprocessing, revealing that the lexicon-based labeling without stopwords
achieved 96% accuracy, while manual labeling without stopwords reached
90%.These findings highlight the high sensitivity of lexicon-based models to the
use of stopwords and their potential to enhance term variation in sentiment
analysis of Generation Z in the workplace via Twitter.