Implementasi Algoritma Klasifikasi C4.5 Untuk Memprediksi Kelayakan Pembelian Kendaraan

  • Egih Sugiatna Universitas Budi Luhur Jakarta
  • Anton Maulana Ibrahim Universitas Budi Luhur Jakarta
  • Ichwansyah Abdul Hadi Universitas Budi Luhur Jakarta
Keywords: Data mining, Decition tree, Naive Bayes, C4.5, classification

Abstract

To choose a vehicle that suits your needs and the funds needed by consumers, you need careful and accurate analysis. The criteria used as a benchmark in choosing a vehicle among other prices, maintenance costs, number of doors, room capacity, baggage area, and vehicle safety level. To process all of these questions is needed a way that can help consumers in choosing the vehicle that best suits their needs. C4.5 algorithm is an algorithm used to compile a decision tree. C4.5 algorithm is used to determine the car to be taken by the buyer according to the background of the purchase criteria (purchase price), maintenance (maintenance costs), doors (number of doors), people (capacity for passenger announcements), lug_boot (delivery area) , safety (vehicle safety level) The results of this study are car purchasing assessment systems that are in line with expectations for potential car buyers in decision making considerations.

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Published
2019-08-30
How to Cite
[1]
E. Sugiatna, A. M. Ibrahim, and I. Abdul Hadi, “Implementasi Algoritma Klasifikasi C4.5 Untuk Memprediksi Kelayakan Pembelian Kendaraan”, jtim, vol. 1, no. 2, pp. 124-132, Aug. 2019.
Section
Articles