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All Journal Telematika Walisongo Journal of Information Technology
Mohamad Tafrikan
UIN Walisongo Semarang
Computer Science & IT Education Engineering

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Journal : Walisongo Journal of Information Technology

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Implementasi Backpropagation ANN dan Algoritma Genetika Terhadap Estimasi Pendapatan Agen Ekspedisi Pengiriman Barang Ahmad Yusuf Naufal; Mohamad Tafrikan; Ariska Kurnia Rachmawati
Walisongo Journal of Information Technology Vol 5, No 1 (2023)
Publisher : Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/wjit.2023.5.1.14452

Abstract

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
Co-Authors Ahmad Yusuf Naufal Ariska Kurnia Rachmawati Asmianto Asmianto Indira Anggriani Mohammad Ghani Yolanda Norasia