Implementasi Backpropagation ANN dan Algoritma Genetika Terhadap Estimasi Pendapatan Agen Ekspedisi Pengiriman Barang

Ahmad Yusuf Naufal; Mohamad Tafrikan; Ariska Kurnia Rachmawati

doi:10.21580/wjit.2023.5.1.14452

Implementasi Backpropagation ANN dan Algoritma Genetika Terhadap Estimasi Pendapatan Agen Ekspedisi Pengiriman Barang

- UIN Walisongo Semarang, Indonesia

* - UIN Walisongo Semarang, Indonesia

- UIN Walisongo Semarang, Indonesia

(*) Corresponding Author

DOI: 10.21580/wjit.2023.5.1.14452

Abstract
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Income is the amount of income received by a person or resident for their work performance during a certain period, whether daily, weekly, monthly or yearly. This research implements the Backpropagation Artificial Neural Network and Genetic Algorithm methods to estimate the income of JNE Express Sekaran agents. Artificial Neural Network and Genetic Algorithm are modern forecasting methods that produce the smallest and most accurate error values. Based on the research that has been done, the Backpropagation Artificial Neural Network method produces the best architectural model, namely 4-10-1 with 4 as the input layer, 10 as hidden neurons, and 1 as the output layer. With epoch 487 obtains an MSE 0,150807. While the Genetic Algorithm method produces the best fitness value is 10209,02 with a population size of 200, crossover probability 0,8, mutation probability 0,03 in the 498th generation and obtains an MSE value of 0,000098. So, it can be predicted that income for the following month is October 2021 of IDR 25.011.603, November 2021 of IDR 20.920.021, and December 2021 of IDR 50.553.019

Keywords: Income, Forecasting, Backpropagation Artificial Neural Network, Genetic Algorithm

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