Vol.8, No.1, February 2019.                                                                                                                                                                             ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333


TEM Journal



Association for Information Communication Technology Education and Science

Car Price Prediction using Machine Learning Techniques


Enis Gegic, Becir Isakovic, Dino Keco, Zerina Masetic, Jasmin Kevric


© 2019 Enis Gegic, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)


Citation Information: TEM Journal. Volume 8, Issue 1, Pages 113-118, ISSN 2217-8309, DOI: 10.18421/TEM81-16, February 2019.


Received: 29 March 2018.
Accepted: 28 January 2019.
Published: 27 February 2019.




A car price prediction has been a high-interest research area, as it requires noticeable effort and knowledge of the field expert. Considerable number of distinct attributes are examined for the reliable and accurate prediction. To build a model for predicting the price of used cars in Bosnia and Herzegovina, we applied three machine learning techniques (Artificial Neural Network, Support Vector Machine and Random Forest). However, the mentioned techniques were applied to work as an ensemble. The data used for the prediction was collected from the web portal autopijaca.ba using web scraper that was written in PHP programming language. Respective performances of different algorithms were then compared to find one that best suits the available data set. The final prediction model was integrated into Java application. Furthermore, the model was evaluated using test data and the accuracy of 87.38% was obtained.


Keywords – car price prediction, support vector machines, classification, machine learning.



Full text PDF >  



Copyright © 2012-2019 UIKTEN, All Rights reserved
Copyright licence: All articles are licenced via Creative Commons CC BY-NC-ND 4.0 licence