Prediction of Employment Status of Vocational High School Graduates Using the Random Forest Algorithm: A Multifactor Analysis of Academic, Social, and Family Factors

Muchamad Firmansyah Tubira; Yulian Findawati; Rohman Dijaya; Yunianita  Rahmwati

doi:10.32664/smatika.v15i02.1804

Penulis

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

DOI:

https://doi.org/10.32664/smatika.v15i02.1804

Kata Kunci:

Faktor Keluarga, Machine Learning, Prediksi, Random Forest, SMK, Status Pekerjaan.

Abstrak

Penelitian ini bertujuan untuk mengembangkan model prediksi status pekerjaan lulusan siswa Sekolah Menengah Atas (SMK) di Indonesia dengan menggunakan analisis multifaktor yang melibatkan kinerja akademik, lingkungan sosial, dan masyarakat. Penelitian ini menggunakan pendekatan kuantitatif dengan algoritma Random Forest untuk mengumpulkan data dalam jumlah besar dan memberikan prediksi yang spesifik. Model tersebut memprediksi status pekerja lulusan siswa SMK sebesar 76%, yang menunjukkan kinerja kerja yang baik. Penelitian ini juga menemukan bahwa faktor masyarakat yang signifikan memengaruhi status pekerjaan lulusan siswa SMK secara signifikan (36,5%), diikuti oleh faktor sosial (35,2%) dan akademik (25,9%). Penelitian ini mendorong sekolah, orang tua, dan pemerintah untuk fokus pada pendidikan holistik SMK, seperti kolaborasi antara sekolah dan industri, untuk meningkatkan status pekerjaan lulusan siswa SMK.

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