Open AccessJaringan Syaraf Tiruan Untuk Memprediksi Nilai Siswa SMA Menggunakan Backpropagation
Author(s) -
Evan Hikler Damanik,
Eka Irawan,
Fitri Rizki
Publication year - 2021
Publication title -
jusikom : jurnal sistem informasi ilmu komputer
Language(s) - English
Resource type - Journals
ISSN - 2580-2879
DOI - 10.34012/jurnalsisteminformasidanilmukomputer.v4i2.1500
Subject(s) - sma* , backpropagation , artificial neural network , value (mathematics) , computer science , mathematics education , artificial intelligence , psychology , machine learning , algorithm
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.