iThenticate Article of Performance of Cans Classification System for Dierent Conveyor Belt Speed using Naïve Bayes

Resti, Yulia (2020) iThenticate Article of Performance of Cans Classification System for Dierent Conveyor Belt Speed using Naïve Bayes. FMIPA Universitas Sriwijaya.

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Abstract

The classification system in the sorting process in the can recycling industry can be made based on digital images by exploring the basic color pixel values of images such as R, G, and B as variable inputs. In real-time, the classification of cans in the sorting process occurs when cans placed on a conveyor belt move at a certain speed. This paper discusses the performance of can classification systems using the Naïve Bayes method. This method can handle all types of variables, including when all variables are continuous. Two types of conveyor belts are designed to get different speeds, and all images of the cans are captured on both conveyor belts. Two models of Bayes naive are built on the basis of different distribution assumptions; the original model (all Gaussian distributed) and the model based on the best distribution. The performance of the classification system is built by dividing data into the learning data and the testing data with a composition of 50:50 in which each data is designed into 50 groups with different percentages on each type of cans using a sampling technique without replacement. The results obtained are first, the speed of the conveyor belt when capturing an image affects the pixel values of red, green, and blue and ultimately affects the results of the classification of cans. Second, not all input variables are Gaussian distributed. The classification system was built using the assumption that the best distribution model for each input variable has a better average accuracy level than the model that assumes all input variables are Gaussian distributed, and the accuracy level of classification on the first speed of conveyor belt with a gear ratio of 12:30 and a diameter of 35 mm has an accuracy that is better than the other speed, both on the original model and the model based on the best distribution. However, it is necessary to test more statistical distribution models to obtain significant results

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:	29 Apr 2023 07:41
Last Modified:	29 Apr 2023 07:41
URI:	http://repository.unsri.ac.id/id/eprint/97968

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