%0 Journal Article
	%A Filiz Ersoz and  Taner Ersoz and  Erkin Guler
	%D 2017
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 127, 2017
	%T Knowledge Discovery and Data Mining Techniques in Textile Industry
	%U https://publications.waset.org/pdf/10008404
	%V 127
	%X This paper addresses the issues and technique for textile industry using data mining techniques. Data mining has been applied to the stitching of garments products that were obtained from a textile company. Data mining techniques were applied to the data obtained from the CHAID algorithm, CART algorithm, Regression Analysis and, Artificial Neural Networks. Classification technique based analyses were used while data mining and decision model about the production per person and variables affecting about production were found by this method. In the study, the results show that as the daily working time increases, the production per person also decreases. In addition, the relationship between total daily working and production per person shows a negative result and the production per person show the highest and negative relationship.
	%P 916 - 920