CLOTH BAG OBJECT DETECTION USING THE YOLO ALGORITHM (YOU ONLY SEE ONCE) V5

  • Rizki Hesananda (1*) Institute Teknologi dan Bisnis BRI
  • Desima Natasya (2) Institute Teknologi dan Bisnis BRI
  • Ninuk Wiliani (3)

    • (*) Corresponding Author
DOI: https://doi.org/10.33480/pilar.v18i2.3019

Keywords: computer vision, cloth bag, yolo, artificial inteligence, trash, detection

Abstract

The use of plastic in modern life is increasing rapidly, causing the number of people who use plastic to increase, one of which is when shopping. The function of plastic bags as packaging for luggage is not comparable to the impact caused by plastic waste in the years to come. Plastic bags take a long time, even hundreds to thousands of years, to completely decompose. In order to support the government's program to reduce the use of plastic bags, this study will discuss how to detect cloth bags as a substitute for plastic bags. In this research, a system will be implemented to detect the use of cloth bags with Roboflow and Yolo v5. After carrying out all stages of the research, it can be concluded that the goodie bag detection model has been successfully created. The detection model was created using the YOLOV5 algorithm. The dataset used consists of 102 goodie bag images. The process model uses 100 epochs with the training result mAP@0.5 is 89.8%. So, in other words, it can be said that YOLO v5 can detect goodie bags very well.

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Author Biography

Rizki Hesananda, Institute Teknologi dan Bisnis BRI

Hi, my name is Hesa. I am a practitioner of the IT industry who is also active in teaching, research and community service as a computer science lecturer. I work as a Web Developer. I have done several types of work such as freelance, corporate companies, ministries and start-ups. I have come to understand, different types of organizations, different needs and their approach to IT needs.

Early in my career, I started a career in the IT industry to apply the computer science I learned in college. I want to know what the real world is like as an IT worker. Not that I'm an expert, but that the industrial world is far more sophisticated than I imagined. I am more and more interested in exploring this field. Then I decided to take my Masters and took some online courses on Computer Science. I work on more than 50 websites, whether it's done in a team or alone, both successful and unsuccessful.

I am a teacher and a learner. At this time, I want to share the knowledge that I got in my master's degree course and my experience from practicing in the IT industry. What I understand is that teaching is the most effective way to learn compared to just reading or taking notes. As a lecturer, I think it is very necessary to understand new fields and always be updated about the outside world. Therefore, now I am starting to explore the fields of Artificial Intelligence such as Data Mining and Computer Vision.

As far as I know, Science and practice in the IT world is developing at an exponential rate. Therefore, the ability to work in teams, adapt to the environment and habits to increase self- capacity are very essential skills.

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Published
2023-02-07
How to Cite
Hesananda, R., Natasya, D., & Wiliani, N. (2023). CLOTH BAG OBJECT DETECTION USING THE YOLO ALGORITHM (YOU ONLY SEE ONCE) V5. Jurnal Pilar Nusa Mandiri, 18(2), 217-222. https://doi.org/10.33480/pilar.v18i2.3019
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Copyright (c) 2023 Rizki Hesananda, Desima Natasya, Ninuk Wiliani

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