iThenticate Article of Dependence in Classification of Aluminium Waste

Resti, Yulia (2015) iThenticate Article of Dependence in Classification of Aluminium Waste. FMIPA Universitas Sriwijaya.

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Abstract

Based on the dependence between edge and colour intensity of aluminium waste image, the aim of this paper is to classify the aluminium waste into three types; pure aluminium, not pure aluminium type-1 (mixed iron/lead) and not pure aluminium type 2 (unrecycle). Principal Component Analysis (PCA) was employed to reduction the dimension of image data, while Bayes' theorem with the Gaussian copula was applied to classification. The copula was employed to handle dependence between edge and colour intensity of aluminium waste image. The results showed that the classifier has been correctly classifiable by 88.33%

Item Type:	Other
Subjects:	#3 Repository of Lecturer Academic Credit Systems (TPAK) > Results of Ithenticate Plagiarism and Similarity Checker
Divisions:	08-Faculty of Mathematics and Natural Science > 44201-Mathematics (S1)
Depositing User:	Mr. Irsyadi Yani, S.T., M.Eng., Ph.D.
Date Deposited:	28 Apr 2023 23:15
Last Modified:	28 Apr 2023 23:15
URI:	http://repository.unsri.ac.id/id/eprint/97982

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