Peningkatan Akurasi Klasifikasi Tingkat Penguasaan Materi Bahan Ajar Menggunakan Jaringan Syaraf Tiruan Dan Algoritma Genetika

Oman Somantri (Department of Informatics, Politeknik Harapan Bersama Tegal)
Slamet Wiyono (Department of Informatics, Politeknik Harapan Bersama Tegal)

Jurnal Teknologi dan Sistem Komputer
Volume 5, Issue 4, Year 2017 (October 2017)

Decision support systems can be applied to perform a lecturer's performance assessment. This research aims to develop a hybrid model using the artificial neural network (ANN) and genetic algorithm (GA) that can be implemented and used as a model of decision support data analysis that produce better accuracy, specifically to assess the lecturer's comprehension of their teaching materials. The use of GA in determining the ANN parameter has increased the accuracy from 85.36% to 85.73%. The training cycle is also reduced to 624 from 1000. The use of this JST-GA model can be applied to provide a better lecture's performance assessment system.