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Digital Object Identifier (DOI) : 10.14569/IJACSA.2013.041105
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 4 Issue 11, 2013.
Abstract: Energy simulation tool is a tool to simulate energy use by a building prior to the erection of the building. Commonly it has a feature providing alternative designs that are better than the user’s design. In this paper, we propose a novel method in searching alternative design that is by using classification method. The classifiers we use are Naïve Bayes, Decision Tree, and k-Nearest Neighbor. Our experiment shows that Decision Tree has the fastest classification time followed by Naïve Bayes and k-Nearest Neighbor. The differences between classification time of Decision Tree and Naïve Bayes also between Naïve Bayes and k-NN are about an order of magnitude. Based on Percision, Recall, F-measure, Accuracy, and AUC, the performance of Naïve Bayes is the best. It outperforms Decision Tree and k-Nearest Neighbor on all parameters but precision.
Ahmad Ashari, Iman Paryudi and A Min Tjoa, “Performance Comparison between Naïve Bayes, Decision Tree and k-Nearest Neighbor in Searching Alternative Design in an Energy Simulation Tool” International Journal of Advanced Computer Science and Applications(IJACSA), 4(11), 2013. http://dx.doi.org/10.14569/IJACSA.2013.041105