Prediksi Status Pekerjaan Lulusan SMK Menggunakan Algoritma Random Forest: Analisis Multifaktor Akademis, Sosial, dan Keluarga - Muchamad Firmansyah Tubira; Yulian Findawati; Rohman Dijaya; Yunianita Rahmwati (SMATIKA JURNAL : STIKI Informatika Jurnal, 2025)
This study aims to develop a prediction model for the employment status of senior high school (SMK) graduates in Indonesia using multifactor analysis involving academic performance, social environment, and society. This study uses a quantitative approach with the Random Forest algorithm to collect large amounts of data and provide specific predictions. The model predicts the employment status of SMK graduates by 76%, indicating good work performance. This study also found that significant community factors significantly affect the employment status of SMK graduates (36.5%), followed by social factors (35.2%) and academic factors (25.9%). This study encourages schools, parents, and the government to focus on holistic SMK education, such as collaboration between schools and industry, to improve the employment status of SMK graduates.