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All Journal Jurnal Inspiration Sistemasi: Jurnal Sistem Informasi Journal of Information Technology and Computer Science (JOINTECS) E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi JUKI : Jurnal Komputer dan Informatika ABSYARA: Jurnal Pengabdian Pada Masyarakat Rambideun : Jurnal Pengabdian Kepada Masyarakat Dedikasi: Jurnal Pengabdian Kepada Masyarakat Malcom: Indonesian Journal of Machine Learning and Computer Science
Andi Asvin Mahersatillah Suradi
Universitas Dipa, Makassar
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Public Health Social Sciences Other

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Journal : JUKI : Jurnal Komputer dan Informatika

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Sistem Deteksi Kantuk Pengemudi Mobil Berdasarkan Analisis Rasio Mata Menggunakan Computer Vision Andi Asvin Mahersatillah Suradi; Samsu Alam; Mushaf Mushaf; Muhammad Furqan Rasyid; Imran Djafar
JUKI : Jurnal Komputer dan Informatika Vol. 5 No. 2 (2023): JUKI : Jurnal Komputer dan Informatika, Edisi Nopember 2023
Publisher : Yayasan Kita Menulis

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Abstract

Driver drowsiness is one of the main causes of motor vehicle accidents. According to National Sleep Foundation records, about 32% of drivers have at least one drowsy driving experience per month. About 25% of traffic accidents are caused by drowsiness while driving each year. The purpose of this study is to design a system that can detect driver sleepiness based on the aspect ratio of the eye with certain parameters using a webcam placed in the car's speedometer area. The methods used are Histogram Oriented Gradients (HOG) and Linear SVM which are in the dlib library which includes machine learning algorithms and uses real time applications. A pre-trained facial landmark detector from the dlib library is used to predict the location of the 68 x-y coordinates that map the facial landmarks to the face zones. The results of this study indicate that the system can be used in real time to detect driver drowsiness with the camera position in the speedometer area at a distance of 50 cm with an average accuracy of 90.4%.
Co-Authors Akbar Bahtiar Anak Agung Gede Sugianthara Andi Syarwani Arham Arifin Arham Arifin Arwansyah Arwansyah Asmah Akhriana Erfan Hasmin Harlina, Sitti Heriadi Heriadi Imran Djafar Indra Samsie Marsa Muhammad Furqan Rasyd Muhammad Furqan Rasyid Muhammad Rizal Muhammad Syukri Mustafa Mushaf Mushaf Mushaf Mushaf Mushaf Novita Sambo Layuk Nurul Aini Salmiati Samsu Alam Santi Santi Sitti Aisa SRI WAHYUNINGSIH PIU Sriwahyuningsi Piu Suci Ramadhani Arifin Sunardi Sunardi