Kusnadi, Adhi and Pratama, Jansen (2017) Implementasi Algoritma Genetika dan Neural Network Pada Aplikasi Peramalan Produksi Mie Studi Kasus : Omega Mie Jaya. Ultimatics : Jurnal Teknik Informatika, 9 (1). ISSN 2085-4552
Full text not available from this repository.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%.
| Item Type: | Article |
|---|---|
| Subjects: | 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 005 Computer Programming |
| Divisions: | Faculty of Engineering & Informatics > Informatics |
| Depositing User: | Administrator UMN Library |
| Date Deposited: | 11 Oct 2021 03:12 |
| Last Modified: | 11 Oct 2021 03:12 |
| URI: | https://kc.umn.ac.id/id/eprint/18611 |
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