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All Journal JURIKOM (Jurnal Riset Komputer)
Hanifah Urbach Sari
STIKOM Tunas Bangsa, Pematangsiantar
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Analisis Jaringan Saraf Tiruan dengan Backpropagation pada korelasi Matakuliah Pratikum Terhadap Tugas Akhir Hanifah Urbach Sari; Agus Perdana Windarto; Irfan Sudahri Damanik
JURIKOM (Jurnal Riset Komputer) Vol 9, No 1 (2022): Februari 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i1.3835

Abstract

Backpropagation is one of the methods contained in a neural network that is able to train dynamic networks using mathematical knowledge based on architectural models that have been developed in detail and systematically. Backpropagation itself is able to accommodate a lot of information that serves as a useful experience. The purpose of this research is to make it easier for AMIK Tunas Bangsa Pematangsiantar students to determine the topic of their final project with practical value so that they can do their final project quickly. So the authors conducted research using correlation in determining the topic of the final project. The data in this study were obtained directly from the AMIK Tunas Bangsa Education academics in Pematangsiantar City. The data used uses data on practical grades of AMIK Tunas Bangsa Stambuk students 2017 from semester 4 to semester 6. There are 5 network architecture models used in this study, namely 5-1-2, 5-6-2, 5-8 -2, 5-10-2, and 5-12-2. From the results of trials conducted with MATLAB software, the best architecture is the 5-1-2 model with an accuracy of 47%. Based on this background, it is hoped that the research results can help students in determining the topic of the final project
Co-Authors Agus Perdana Windarto Irfan Sudahri Damani, Irfan Sudahri