The Application of ANN Predicts Students' Understanding of Subjects During Online Learning Using the Backpropagation Algorithm at SMAN 1 Perbaungan - rendiarno, rendiarno; Fahmi, Hasanul (Yayasan Kita Menulis, 2022)
This study is a study to predict the level of students' understanding of the subjects given by educators at SMAN 1 Perbaungan. This study aims to determine how far the level of understanding of students in understanding lessons, especially during the current covid-19 pandemic, which is a process of teaching and learning activities carried out from their respective homes or using online learning media. The method used is an artificial neural network with Backpropagation algorithm with variables used are knowledge values, skill scores, mid-semester exam results, end-semester exam results, and attitude scores. The five variables are used to support predicting the level of student understanding of the subject using the single layer Backpropagation Algorithm. The architectural model used is 5-2-1 with a success accuracy of 85%. The smaller the error value that is close to 0, the smaller the deviation of the results of the Artificial Neural Network with the desired target.