• Akmal Dirgantara (1*) Ilmu Komputer STMIK Nusa Mandiri
  • Syarifudin Herdyansyah (2) Ilmu Komputer STMIK Nusa Mandiri
  • Rasenda Rasenda (3) Ilmu Komputer STMIK Nusa Mandiri

  • (*) Corresponding Author
Keywords: Neural Network, Used Car, Backpropagation, Classification


Considering the need for cars in big cities is increasing and the price of 4-wheeled vehicles is relatively expensive, used cars are a good alternative solution to offer. But in business we cannot just buy stock for a car showroom, for example, especially with a limited budget, car showroom entrepreneurs must do a thorough analysis to save the budget to open a showroom and prevent losses. This article helps open the car showroom to determine which cars are suitable as stock to be displayed in the showroom with the parameters of buying, maintenance, doors, boot lugs, and safety. That predicted using 1728 artificial neural network methods data obtained from the UCI repository with a fairly high degree of accuracy that is equal to 98.26%. This is quite efficient compared to the showroom owner who must conduct a survey in advance and ask 1 per 1 person to survey the interest in receiving a car.


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How to Cite
Dirgantara, A., Herdyansyah, S., & Rasenda, R. (2020). KLASIFIKASI PENERIMAAN MOBIL BEKAS BERDASARKAN METODE NEURAL NETWORK. Jurnal Riset Informatika, 2(1), 43-48. https://doi.org/10.34288/jri.v2i1.119
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