Implementasi Algoritma Backpropagation Prediksi Kegagalan Siswa Pada Mata Pelajaran Matematika - Melladia Melladia; Iis Roza Mardani (Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2018)
Students become those who can advance the nation. Schools and teachers are very helpful in creating smart and competent students. But often found students who fail, one of which is in the eyes of mathematics. With problems with students Mathematics study researchers want to help solve problems by using predictions on math subjects. In this study the researchers chose the object of research, namely in Padang State Middle School 39. This is quite a problem for students when teaching and learning mathematics subjects. Students do not understand mathematics and this problem will make students' grades decrease. By using student value data, a model is designed to predict students against mathematics subjects. The model uses the backpropagation algorithm. Data variables are taken from students' mathematical currency data, namely assignment 1, assignment 2, average, mid-semester and final semester grades. The data generated is 1 semester data and the number of students predicted is 30 students. The prediction results using the best model are training pattern data 5-2-1 with EPOCH process = 58 and MSE achievement when payment with MSE = 0,00989892 with an accuracy of 99,9901011. it can be cited that the backpropagation algorithm can be used to predict student errors in the eye Mathematics lessons as a guide for teachers