PREDICTION OF STUDENT PASSING SCORE USING BACKPROPAGATION METHOD (CASE STUDY: SMP NEGERI 1 SEI BINGAI LANGKAT) - Sembiring, Jams David Pindona; Gultom, Imeldawaty; Sembiring, Arnes (Yayasan Bina Internusa Mabarindo, 2024)
Education is one of the most important aspects in life in order to form quality human resources and be able to follow the flow of the increasingly advanced era. Students ' passing scores can be used as useful data to see the development of children who will continue their education at the next level, with the results of high passing scores, can create confidence in these students to continue the level of education they want. But not all students get the passing score in accordance with what they want, due to several factors, for example lack of discipline and not too focused on pursuing grades and some are busy working so that school is forgotten. From these conditions, the SMP Negeri 1 Sei Bingai Langkat need to create a system that can predict the passing score of students who will come. The results of these predictions can be used to recommend a decent and good school for students to enter with a high enough passing score. The process in predicting the passing score of students can be done with a computerized system, one of the processes that can be done is the application of Artificial Neural Networks (Ann) with the use of the method Backpropagation process. With the construction of the system is expected to facilitate and assist SMP Negeri 1 Sei Bingai Langkat in knowing the passing score of their students, so that it can be used as a basis in recommending a school that they deserve to enter as the next level of Education. From the research conducted, the results of the number of output layer errors is still large and has not met the target error of 0.001, namely the value of Mathematics for school exams (US) Ade Christy in Junior High School (SMP) Negeri 1 Sei Bingai Langkat are as follows: maximum value (a) : 99 minimum value (b) : 70.