Analisis Sentimen Masyarakat terhadap Instruksi Gubernur Jakarta tentang ASN Wajib Gunakan Transportasi Umum Menggunakan Algoritma Support Vector Machine - Oktavian, Nur; Surapati, Untung; Setiawan, Kiki (Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh, 2025)
Social media has become the primary means for people to express their opinions on public policies. One policy that has generated mixed reactions is DKI Jakarta Governor Instruction Number 6 of 2025, which requires civil servants (ASN) to use public transportation every Wednesday. This study aims to analyze public sentiment towards this policy using the Support Vector Machine (SVM) algorithm. Data was collected from social media X using purposive sampling technique using related keywords during the period May-July 2025. Then processed through the stages of cleansing, tokenizing, stopword removal, stemming, and transformation into numerical form using TF-IDF. Of the 800 tweets collected, 600 positive opinions and 200 negative opinions were obtained. Then, the data was classified using the Support Vector Machine algorithm. Thus, the research that has been conducted obtained an accuracy of 76.00%, and an AUC of 0.725. These findings are expected to not only provide accurate sentiment classification, but also provide practical input for the government to evaluate the effectiveness of policies, improve socialization strategies, and measure the level of public acceptance of ASN transportation policies.