Karya
Judul/Title Performance Comparison between Naive Bayes, Decision Tree and k-Nearest Neighbour in Searching Alternative Design in an Energy Simulation Tool
Penulis/Author Prof. Dr. Techn. Ahmad Ashari, M.I.Kom. (1) ; Iman Paryudi (2); A Min Tjoa (3)
Tanggal/Date 2013
Kata Kunci/Keyword
Abstrak/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 experiments hows 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.
Rumpun Ilmu Ilmu Komputer
Bahasa Asli/Original Language English
Level Internasional
Status
Dokumen Karya
No Judul Tipe Dokumen Aksi
116IJACSA_Volume4No11-November2013-fullpaper.pdf[PAK] Full Dokumen
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