Analisis Sentimen Komentar Netizen Terhadap 17+8 Tuntutan Rakyat Pada X Menggunakan Naive Bayes Classifier - Fransisco Lucky Halawa; Rudi Heriansyah; Indah Permatasari (Teknik: Jurnal Ilmu Teknik dan Informatika, 2026)
This study analyzes netizen sentiment concerning the 17+8 public aspirations circulating the digital platform X spanning the period from August 18 through October 31, 2025. 1,837 comments obtained through scraping method. Classification Research stages include data preprocessing, sentiment weighting based on lexicon, and feature extraction using TF-IDF. Data 80% used for learning purposes and the remaining 20% utilized for validation. The findings reveal that the majority of comments, amounting to 81.14%, contained negative sentiment, while the remaining 18.86% were positive. The outcomes demonstrate that community reactions toward the 17+8 People's Demands were dominated by unsupportive views. From a theoretical standpoint this scholarly work offers to enriching knowledge concerning public opinion classification on political issues through a computational approach, while also serving as a reference for future research focused on improving the accuracy of sentiment analysis related to political dynamics and the behavior of state institutions.