Jurnal ICT : Information Communication & Technology
Vol 18, No 1 (2019): JICT-IKMI, Juli 2019

Optimasi Parameter Artificial Neural Network Menggunakan Algoritma Genetika Untuk Prediksi Kelulusan Mahasiswa

Ali, Irfan (Unknown)
Sularto, Lana (Unknown)



Article Info

Publish Date
07 Aug 2019

Abstract

It is difficult to predict student graduation status in a college. Higher education needs to predict student behavior from active students so that it can be seen the failure factor of students who do not graduate on time. Data mining classification techniques used to predict students are using artificial neural networks. Artificial neural network is one method to predict student graduation. This researcher tries to apply artificial neural network methods using genetic algorithms to predict student graduation. In this study using the learning rate parameter 0.1 with optimization using genetic algorithms then evaluating to get accuracy. The results of this study get an accuracy value for artificial neural network models of 71.48% and accuracy for artificial neural network models based on genetic algorithms by 99.33% with an accuracy difference of 27.85%.

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Journal Info

Abbrev

jict-ikmi

Publisher

Subject

Computer Science & IT

Description

Jurnal ICT : Information Communication & Technology (JICT) (p-ISSN: 2302-0261, e-ISSN: 2303-3363 ) is a scientific journal and open access journal published by Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) of STMIK IKMI Cirebon, Indonesia. Jurnal JICT covers the field of Informatics, Computer ...