Penerapan Algoritma Machine Learning Untuk Penjurusan Siswa Baru Sekolah Menengah Kejurusan Berdasarkan Nilai Raport dan Psikotest
DOI:
https://doi.org/10.22441/jitkom.2023.v7i1.008Keywords:
Penjurusan, Algoritma, Akurasi, PerbandinganAbstract
Penelitian ini bertujuan untuk mengevaluasi keefektivan sistem penjurusan siswa di Sekolah Menengah Kejuruan (SMK) dengan menggunakan empat algoritma machine learning, yaitu K-Nearest Neighbor, Naive Bayes, Support Vector Machine, dan Random Forest. Hasil penelitian menunjukkan bahwa algoritma Random Forest memiliki akurasi terbesar dibandingkan algoritma lainnya. Saat ini, proses penjurusan siswa di SMK tempat penelitian ini dilakukan, masih diprosessecara manual melalui perhitungan nilai raport, nilai tes mandiri, dan nilai psikotes. Proses penjuruan secara manual tersebut memakan waktu yang cukup lama. Implementasi algoritma Random Forest dapat menjadi solusi untuk mempercepat proses penjurusan siswa di SMK tersebut. Algoritma Random Forest memiliki akurasi terbaik di antara algoritma lain, yaitu 37% hampir mencapai 38%.References
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