Application of Artificial Neural Networks to Predict Exports of Four-Wheeled Vehicles by Destination Country

Authors

  • Ema Meyliza STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
  • Eka Irawan STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
  • Dedi Suhendro STIKOM Tunas Bangsa, Pematangsiantar, Indonesia

DOI:

https://doi.org/10.55123/jomlai.v1i3.914

Keywords:

Motor Vehicle, Prediction, Back-propagation, Export, Country of Destination

Abstract

Motorized vehicles are vehicles that are energized through machines and used for land transportation,, as well as movement through technical equipment in the form of electric motors and other tools that have the function of converting an energy source into power to drive the vehicle. This study aims to determine the results of the predicted number of four-wheeled vehicle exports by destination country in the years to come. The research data used is data on exports of four-wheeled motor vehicles by destination country for 2012-2020. The algorithm used in this research is an artificial neural network with Back-propagation method. The best architectural model used in this research is architect 4-4-1 with an accuracy rate of 82% epoch of 2261 iterations and MSE of 0.0081876. So it can be concluded that the model can be used to predict export data for four-wheeled vehicles by destination country.

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Published

2022-10-18

How to Cite

Meyliza, E., Irawan, E., & Suhendro, D. (2022). Application of Artificial Neural Networks to Predict Exports of Four-Wheeled Vehicles by Destination Country. JOMLAI: Journal of Machine Learning and Artificial Intelligence, 1(3), 239–244. https://doi.org/10.55123/jomlai.v1i3.914

Issue

Vol. 1 No. 3 (2022): September

Section

Articles

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