Year: 2021
Type: article
Abstract: A student's mastery of a subject greatly influences the marking given by the teacher / teacher concerned. The need for instructors or teachers to monitor every value of students who are taught science in their respective fields. With the rapid development of technology, it is very helpful for teachers in knowing or predicting the value that students will get related. This study aims to apply the performance of backpropagation artificial neural networks in predicting the value of students of SMA N 1 Sidamanik with various models and minimizing their errors. In this study the authors used data on student grades from SMA N 1 Sidamanik. In processing data values, the authors use artificial neural networks with backpropagation algorithms as logical steps to predict student National Exam Scores in SMA N 1 Sidamanik. The main problem in this study is the decline in student grades in some subjects, in the future students will experience difficulties in reaching the desired university or high school.
Authors: Evan Hikler Damanik, Eka Irawan, Fitri Rizki
Institution: STIKOM Tunas Bangsa
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W4206498458