CLASSIFICATION OF STUDENT’S AIR TRAFFIC CONTROL SKILL USING LOGISTIC REGRESSION

Liber Tommy Hutabarat (Akademi Teknik dan Keselamatan Penerbangan (ATKP) Medan)
Hairul Amren S. (Akademi Teknik dan Keselamatan Penerbangan (ATKP) Medan)
Marzuki Sinambela (Universitas Sumatera Utara)
Tonni Limbong (Universitas Katolik Santo Thomas)

METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi
Vol. 3 No. 2 (2019): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi

The classification of student’s air traffic control skills at Akademi Teknik dan Keselamatan Penerbangan Medan (ATKP) is very interesting to evaluate and look at the performance of the student. In this study, we compute the student’s air traffic control (ATC) skill data to classify and evaluate the model and performance of the dataset. The computation of the dataset using the logistic regression approach based on Sk-learn by training and test data. The data was collected from ATKP for twenty samples. The result of this study indicates the logistic regression classifier is the best algorithm for this classification problem, offering good values in terms of accuracy, true negative rate, and true positive rate.