Prediksi Nilai Kelulusan Sekolah Menengah Atas Menggunakan Metode Backpropagation
Abstract
Schools play an important role in providing the best education as well as developing and creating the character of a child who will become the nation's successor in the future. Starting from providing online education, making learning materials as efficient as possible and not burdening students in learning. But every level of education requires evaluation as a benchmark, one of which is the Regional School Examination. This study aims to create a system that can predict exam scores. This system uses the Artificial Neural Network method with the Backpropagation algorithm to predict student grades. Based on the test results, the neural network model has data management with five inputs and one output. The input value is obtained from the student's grades from semester one to semester five. The output value is the predicted score of the Regional School Examination. From a number of tests, the highest accuracy level was 89.8579% at the 100th epoch. With the development of this application, it is hoped that it can help improve the efficiency of MA Imam Syafi'i learning
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