Open AccessAnalysis of building energy efficiency dataset using naive bayes classification classifier
Author(s) -
Budi Prasetiyo,
Alamsyah Alamsyah,
Much Aziz Muslim
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1321/3/032016
Subject(s) - naive bayes classifier , glazing , roof , mean squared error , cooling load , bayesian probability , statistics , bayes' theorem , environmental science , computer science , mathematics , pattern recognition (psychology) , artificial intelligence , structural engineering , engineering , support vector machine , civil engineering , mechanical engineering , air conditioning
The phenomenon of global warming has become a very important and serious issue in recent years. One effort to reduce emissions by applying the green architecture concept to buildings. The purpose of this paper is to classify energy efficiency data sets. The method used by the Naïve Bayesian Classifier algorithm. Results obtained by Kappa statistics Y1 (0.3357) and Y2 (0.4203); Mean absolute error Y1 (0,0368), Y2 (0,0335); Root mean squared error Y1(0,1491), Y2(0,1412). The results of the analysis showed overall height, relative compactness, wall area, and glazing area affected the heating and cooling loads, while the surface area affected the heating load and the roof area affected the cooling load.