Tingkat Korelasi Prestasi Akademik Terhadap Siswa SMP Menggunakan Metode Backpropagation
DOI:
https://doi.org/10.37034/jsisfotek.v3i3.52Keywords:
Neural Network (ANN), Backpropagation, Correlation, Semester Value, Software MatlabAbstract
Student academic achievement plays a very important role in determining the quality of a school. Student grades sometimes change every semester, there are increases and decreases. There is an assumption that students whose grades are in the previous semester will be in the next semester and vice versa. is expected to make it easier for us as educators to see the extent to which changes in student academic achievement. The data tested is the data of 60 class VII students in 2 semesters. Furthermore, it will be tested using the MatLab Application, then the results of the changes that occur will come out. The results of this study found that they did not know the value of semester 1 with the value of semester 2 TP. 2019/2020 is very good with an architectural pattern of 10-10-1 with a value of 95.3%. So students who excel in semester 1 are likely to excel in the following semester. So that it can help the school in seeing the Correlation Level of Student Academic Achievement at SMPN 3 Lengayang.
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