Jaringan Saraf Tiruan Untuk Memprediksi Tingkat Pemahaman Sisiwa Terhadap Matapelajaran Dengan Menggunakan Algoritma Backpropagation

Abstract

Prediction of students 'understanding of the subject is important to know the extent to which the students' understanding of the subjects presented by educators when teaching and learning activities and to determine the ability of educators in delivering subjects. Artificial Neural Network to predict the level of students' understanding of subjects using backpropagation learning algorithm uses several variables: Knowledge, skills / abilities, assessment and workload and guidance and counseling. Backpropagation learning algorithm is applied to train eight indicators to predict the level of students' understanding of the subjects. The test results obtained by the student's understanding level prediction accuracy rate of 90% with a 6-5-1 architecture.