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All Journal Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Vivi Auladina
STIKOM Tunas Bangsa, Pematangsiantar, Sumatera Utara, Indonesia
Computer Science & IT Control & Systems Engineering

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Penerapan Algoritma Backpropagation Dalam Memprediksi Jumlah Pengguna Kereta Api Di Pulau Sumatera Vivi Auladina; Jaya Tata Hardinata; M. Fauzan
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 2, No 1 (2021): Edisi Januari
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v2i1.58

Abstract

The purpose of this study is to analyze and test whether the number of train passengers in Indonesia can be predicted by using artificial intelligence techniques. In this study, the artificial intelligence technique used is the Artificial Neural Network Technique (ANN) with the Backpropagation method. Artificial neural network is a method that has been widely used to solve forecasting cases. The main difficulties in implementing neural network methods in forecasting are finding the right architectural combination, determining the appropriate learning rate parameter values and selecting the optimal training algorithm. The research data is secondary data sourced from the bps.go.id website from 2006 - 2019. The data in this study were computerized using the matlab application. From the 5 architectural models used, the best model based on computerized results with the Matlab application is 3-3-1 with an output value of 0.0215923 MSE. The accuracy of the truth obtained is 92%.
Co-Authors Jaya Tata Hardinata M. Fauzan