Path: Top -> Journal -> Jurnal Nasional Teknik Elektro dan Teknologi Informasi -> 2019 -> Vol 8, No 4

Integrasi Gradient Boosted Trees dengan SMOTE dan Bagging untuk Deteksi Kelulusan Mahasiswa

Journal from gdlhub / 2020-06-02 10:51:37
Oleh : Achmad Bisri, Rinna Rachmatika, JNTETI
Dibuat : 2020-06-02, dengan 1 file

Keyword : Gradient Boosted Trees, SMOTE, Bagging, Deteksi Kelulusan, Ketidakseimbangan Kelas
Url : http://ejnteti.jteti.ugm.ac.id/index.php/JNTETI/article/view/529
Sumber pengambilan dokumen : WEB

Education has an important role in life. Pamulang University is a university which provides education at affordable cost. However, based on student academic performance data, there is imbalance in class between the number of students who graduate on time and students who can’t graduate on time, on various study programs. In this paper, an implementation of SMOTE and bagging techniques was conducted on the Gradient Boosted Trees (GBT) classification method for handling the class imbalance problem. The proposed method is able to provide significant results with an accuracy of 80.57% and an AUC of 0.858, in the category of good classification.

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PropertiNilai Properti
ID Publishergdlhub
OrganisasiJNTETI
Nama KontakHerti Yani, S.Kom
AlamatJln. Jenderal Sudirman
KotaJambi
DaerahJambi
NegaraIndonesia
Telepon0741-35095
Fax0741-35093
E-mail Administratorelibrarystikom@gmail.com
E-mail CKOelibrarystikom@gmail.com

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