iThenticate Article of Automatic Identification of Plastic Waste by HSV Colour

Resti, Yulia (2022) iThenticate Article of Automatic Identification of Plastic Waste by HSV Colour. FMIPA Universitas Sriwijaya.

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Abstract

People don’t enjoy living without plastic nowadays. It happens because, in almost every industry, plastic has become a commonly used material. However, at present, it causes the waste of plastic to increase. The process needs to be recycled to reduce the contamination of plastic waste. The manual recycling method has a high possibility of human error, therefore, this automatic system is designed to minimize human error. This research applies Artificial Neural Network (ANN) with three types of plastic to construct an automatic framework to classify and catego�rized plastic waste. This study also used HSV color space with six input character�istics (RHSV, GHSV, BHSV, mean2, entropy, and variance). The database analysis collected by the training and testing process focused on the implementation of an automatic identification and classification method for plastic bottles, and the rate of the percentage of progress achieved from the training process is 65.3%. The research process’s percentage effectiveness is 57%

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 23:14
Last Modified:	28 Apr 2023 23:14
URI:	http://repository.unsri.ac.id/id/eprint/97940

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