IMPLEMENTASI METODE K-NEAREST NEIGHBORS (KNN) PADA SISTEM SORTIR BOTOL PLASTIK OTOMATIS BERBASIS CITRA

NURFARIZI, MUHAMMAD FAA'IQ and Yani, Irsyadi (2025) IMPLEMENTASI METODE K-NEAREST NEIGHBORS (KNN) PADA SISTEM SORTIR BOTOL PLASTIK OTOMATIS BERBASIS CITRA. Undergraduate thesis, Sriwijaya University.

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Abstract

Environmental problems due to the accumulation of plastic waste, especially plastic bottles that are difficult to decompose naturally, encourage the need for an efficient waste management system to support a circular economy. One important step in the recycling process is the sorting of plastic bottles based on their type. This research aims to design and implement a digital image-based automatic sorting system using the K-Nearest Neighbors (KNN) method to classify three types of plastic, namely PET (Polyethylene Terephthalate), HDPE (High-Density Polyethylene), and PP (Polypropylene). The system is built in the form of a physical prototype consisting of a conveyor belt, web camera, mini computer, mini monitor, and wireless keyboard, where the camera captures real-time images of bottles and the system processes them using RGB color images converted to HSV. The dataset is 150 images, divided into 120 training images and 30 test images, and processed using Python libraries such as OpenCV, NumPy, and scikit-learn. The classification results show that the KNN method with a value of K = 1 is able to classify plastic bottle types with an accuracy of 83%. The system works in real-time and proved to be stable at a conveyor speed of 0.04 m/s, making it quite efficient for plastic bottle sorting applications. In conclusion, the system is capable of automatic and economical classification of plastic bottles with high accuracy, and can serve as a basis for the development of more sophisticated plastic waste sorting systems. Suggestions for further development include optimizing lighting and image capture, increasing sorting speed, and testing with larger and more varied datasets, so that the system can be more adaptive to real conditions in the field.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	K-Nearest Neighbors (KNN), sistem sortir botol plastik otomatis, pengolahan citra digital, RGB ke HSV, botol plastik PET, HDPE, PP
Subjects:	T Technology > TJ Mechanical engineering and machinery > TJ1125-1345 Machine shops and machine shop practice > TJ1180 Machining, Ceramic materials--Machining-Strength of materials-Machine tools-Design and construction > TJ1180.I34 Machining-Machine tools-Numerical control-Computer integrated manufacturing systems-Artificial intelligence T Technology > TJ Mechanical engineering and machinery > TJ170-179 Mechanics applied to machinery. Dynamics T Technology > TJ Mechanical engineering and machinery > TJ210.2-211.47 Mechanical devices and figures. Automata. Ingenious mechanisms. Robots (General) T Technology > TJ Mechanical engineering and machinery > TJ241-254.7 Machine construction (General) > TJ241.I59 Machine design--Congresses. Production engineering--Congresses
Divisions:	03-Faculty of Engineering > 21201-Mechanical Engineering (S1)
Depositing User:	Muhammad Faa'iq Nurfarizi
Date Deposited:	20 Aug 2025 04:08
Last Modified:	20 Aug 2025 04:08
URI:	http://repository.unsri.ac.id/id/eprint/183013

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