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All Journal Conference on Innovation and Application of Science and Technology (CIASTECH) Informatika : Jurnal Informatika, Manajemen dan Komputer Systemic: Information System and Informatics Journal Jurnal Intake : Jurnal Penelitian Ilmu Teknik dan Terapan Jurnal Aplikasi Teknologi Informasi dan Manajemen (JATIM) Jurnal Penelitian Inovatif Ilmu Komputer untuk Masyarakat TRILOGI: Jurnal Ilmu Teknologi, Kesehatan, dan Humaniora Nusantara Journal of Computers and its Applications
Honainah Honainah
Universitsa Nurul Jadid
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Public Health Social Sciences Other

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Journal : TRILOGI: Jurnal Ilmu Teknologi, Kesehatan, dan Humaniora

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Deteksi Otomatis Terhadap Pelanggaran Pembuang Sampah Menggunakan Metode You Only Look Once (YOLO) Honainah Honnainah; Ratri Enggar Pawening
TRILOGI: Jurnal Ilmu Teknologi, Kesehatan, dan Humaniora Vol 4, No 2 (2023)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/trilogi.v4i2.6676

Abstract

Disposing of garbage is a bad thing that can spoil the view, cause bad smells, cause low to high level flooding, cause various diseases and can pollute the environment. Even though the ban on disposing of trash has been implemented, there are still many who violate it. The importance of avoiding this makes a study aimed at automatically detecting violations of waste disposal. The method used is YOLOv5, this method is an algorithm that can identify objects with high accuracy, besides that it can also carry out tracking processes in the form of bounding boxes for objects in real time. The programming language used is Google Colaboratory. The dataset used is in the form of 800 images and 2 videos. After testing the results of the research using the You only look once (YOLO) method, the best results were obtained on the parameter batch 5 epochs 5 with an accuracy of 95%. From these results it can be concluded that the use of the YOLO method is very accurate when applied to the detection process of an object.
Co-Authors Alifia Nur Afni Lismawati Amilia agustin Anani Asmani Andi Wijaya Anis Yusrotun Nadhiroh Arika Ramadhany Ato’illah Ato’illah Fahrial Faqih Romadhoni Khuzairi Mun’im Moch. Jasri Moh Jasri Nurul Imaniyah Putri Eka Aliyatul Himma Ratri Enggar Pawening Siti Romelah Tijaniyah Tijaniyah Wahab Sya’roni Yaqin, Moh. Ainol Yuda Asror Maulana