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All Journal Jurnal Ilmiah WUNY JURNAL DERIVAT: JURNAL MATEMATIKA DAN PENDIDIKAN MATEMATIKA JAM : Jurnal Aplikasi Manajemen Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Pengabdian Masyarakat Asia GANESHA: Jurnal Pengabdian Masyarakat JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Ilmiah Bisnis dan Ekonomi Asia (Jibeka)
Yudistira Arya Sapoetra
Program Pascasarjana Fakultas Ekonomi dan Bisnis, Universitas Brawijaya
Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Public Health Social Sciences Other

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Journal : JURNAL DERIVAT: JURNAL MATEMATIKA DAN PENDIDIKAN MATEMATIKA

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Random Number Generator Untuk Bobot Metode Conjugate Gradient Neural Network Sapoetra, Yudistira Arya; Habibi, Azwar Riza; Hakim, Lukman
Jurnal Derivat: Jurnal Matematika dan Pendidikan Matematika Vol 4, No 1 (2017): Jurnal Derivat (Juli 2017)
Publisher : Pendidikan Matematika Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (931.994 KB) | DOI: 10.31316/j.derivat.v4i1.161

Abstract

This research develops the theory of NN (neural network) by using CG (conjugate gradient) to speed up the process of convergence on a network of NN. CG algorithm is an iterative algorithm to solve simultaneous linear equations on a large scale and it is used to optimize the process of the network on backpropagation. In the process, a Neural netwok doing random weighting on the weight of v and w  and this weight will have an effect on the speed of convergence of an algorithm for NN by the method of CG. Furthermore, generating the random numbers to take a sample as a generator in this research of neural network by using uniform distribution (0,1) methods. Therefore, the aims of this research are to improve the convergence on NN weighting using numbers which are generated randomly by the generator and the will be corrected with the CG method.Keywords: neural network, backpropagation, weighting, conjugate gradient
Co-Authors . Surachman Anjaningrum, Widiya Dewi Azwar Riza Habibi, Azwar Riza Christin Susilowati Farokhah, Lia Kabalen, Nicholaus Wayong Kabelen, Nicholaus Wayong Lukman Hakim M.R., Moh. Irsyad Fahmi