Metode SVM Berbasis PSO untuk Meningkatkan Prediksi Ketepatan Waktu Kelulusan Mahasiswa
endang supriyadi · 2018
This scientific article discusses how the swarm optimization particle method can improve accuracy in predicting student graduation accuracy. This is done in order to anticipate the decrease in the number of students in their lectures. The experimental results have shown that particle swarm optimization (PSO) can improve the accuracy of the support vector machine method from 80.14% accuracy to 82.05% so that there is an increase of accuracy of 1.91%.