Prediksi Status Pekerjaan Lulusan SMK Menggunakan Algoritma Random Forest: Analisis Multifaktor Akademis, Sosial, dan Keluarga

Muchamad Firmansyah Tubira (Informatika, Universitas Muhammadiyah Sidoarjo, Indonesia)
Yulian Findawati (Informatika, Universitas Muhammadiyah Sidoarjo, Indonesia)
Rohman Dijaya (Informatika, Universitas Muhammadiyah Sidoarjo, Indonesia)
Yunianita Rahmwati (Universitas Muhammadiyah Sidoarjo)

Smatika Jurnal : STIKI Informatika Jurnal
Vol 15 No 02 (2025): SMATIKA Jurnal : STIKI Informatika Jurnal

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.