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Jansen Pratama
Universitas Multimedia Nusantara
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Implementasi Algoritma Genetika dan Neural Network Pada Aplikasi Peramalan Produksi Mie Adhi Kusnadi; Jansen Pratama
Ultimatics : Jurnal Teknik Informatika Vol 9 No 1 (2017): Ultimatics: Jurnal Ilmu Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (580.149 KB) | DOI: 10.31937/ti.v9i1.562

Abstract

Companies that produce products must be able to regulate the amount of production so that it have plan production. Therefore, it is necessary to be able to predict the amount of production. This research aims to create an application that is useful in determining the amount of production. These applications using genetic algorithms and neural network. Genetic algorithm is used to optimize the weights in the neural network. From the test results, this application uses network with 12 inputs, 5 neuron in first hidden layer, 3 neurons in the second hidden layer, and 3 neurons in the last hidden layer. Then for the genetic algorithm parameters used were 10 individuals, 50 generations, crossover probability 0.8 and mutations probability 0.1. Based on the test results, this application has the forecasting’s accuracy rate reaches 86%. Keyword : forecasting, production forecasting, genetic algorithm neural network, optimization.
Co-Authors Adhi Kusnadi