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All Journal INTI Nusa Mandiri Jurnal Pengabdian Masyarakat Bangsa Jurnal Elektro Kontrol (ELKON)
Abdillah, Mokhammad Nurkholis
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Journal : INTI Nusa Mandiri

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DETEKSI RUPIAH EMISI 2022 UNTUK DISABILITAS NETRA MENGGUNAKAN YOLOV5M DENGAN OUTPUT SUARA Mahfuzh, Muhammad Farhan; Abdillah, Mokhammad Nurkholis; Fatkhurrozi, Bagus
INTI Nusa Mandiri Vol. 19 No. 1 (2024): INTI Periode Agustus 2024
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v19i1.5295

Abstract

People with visual disabilities have difficulty recognizing rupiah denominations using blind codes due to differences in paper size for each denomination, wrinkled paper, and variations in blind codes for different emission years.. The proposed method uses the YOLOv5m algorithm as well as Google Text to Speech (GTTS) as voice output. The aim of the research is to find a model with the best precision value from YOLOv5m in detecting the 2022 emission rupiah and integrate it into GTTS to produce nominal rupiah sounds. The model was trained with the main image dataset, namely 700 images of rupiah emissions in 2022 taken at an angle of 1200. Next, the model was tested to recognize seven nominal amounts, namely IDR 1,000, IDR 2,000, IDR 5,000, IDR 10,000, IDR 20,000, IDR 50,000, and IDR 100,000. The test results show that the best YOLOv5m model is the one that has been trained using the main dataset (700 images) and supplemented with a multi-class image dataset (250 images) and background images (30 images). This model has a precision value of 82% when testing in real time. This research succeeded in applying the YOLOv5 algorithm which is integrated with Google Text to Speech to detect the image of 2022 emission rupiah banknotes.
Co-Authors Adji Nugraha, Maulana Yusuf Samudra Bagus Fatkhurrozi Ika Setyowati, Ika Mahfuzh, Muhammad Farhan Setiawan, Hery Teguh