Identifikasi Mahasiswa Berprestasi Menggunakan Algoritma Backpropagation

Riki Winanjaya (STIKOM Tunas Bangsa, Pematangsiantar)

RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI
Vol. 1 No. 2 (2020): RESOLUSI Nopember 2020

Determination of performance students requires a gradual process. To speed up the process of determining performance students, the Artificial Neural Network method was used. The method used is Backpropagation on student data on AMIK Tunas Bangsa Pematangsiantar. This research produced five architectural models, they are 5-5-1, 5-6-1, 5-7-1, 5-8-1, 5-9-1 and 5-10-1 with models 5-5-1 the best in accelerating the process of determining performance students. So that this architectural model is best to be used to determine the better performance students