Analisis Sentimen Terhadap Istana Garuda Di Ibukota Nusantara (IKN) Menggunakan Algoritma Random Forest Dan Support Vektor Machine - Jihansyah, Muhamad; Agung Budi Susanto; Arya Adhyaksa Waskita (Universitas Pamulang, 2025)
ABSTRACT The relocation of Indonesia's capital city (IKN) to East Kalimantan is a national strategic project that has sparked diverse public opinions, particularly regarding the construction of Garuda Palace. This study aims to analyze public sentiment toward the Garuda Palace project using Random Forest and Support Vector Machine (SVM) algorithms and to compare their performance based on accuracy, precision, recall, and F1-score. This research offers three key novelties. First, it focuses on public opinion regarding the Garuda Palace project at IKN, which is underexplored in both local and international literature. Second, the use of Inset and Senti labeling techniques introduces a novel approach to sentiment categorization. Third, the comprehensive evaluation of Random Forest and SVM performance provides new insights into their effectiveness in large-scale infrastructure sentiment analysis in Indonesia. The methodology consists of five stages: (1) Data collection through web scraping from Twitter (July-August 2024) using keywords related to