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All Journal MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer INTERACTION: Jurnal Pendidikan Bahasa
Muhammad Naufal
Dian Nuswantoro University, Semarang
Computer Science & IT Education Languange, Linguistic, Communication & Media

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Drowsiness Detection Based on Yawning Using Modified Pre-trained Model MobileNetV2 and ResNet50 Hepatika Zidny Ilmadina; Muhammad Naufal; Dega Surono Wibowo
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 22 No 3 (2023)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i3.2785

Abstract

Traffic accidents are fatal events that need special attention. According to research by the National Transportation Safety Committee, 80% of traffic accidents are caused by human error, one of which is tired and drowsy drivers. The brain can interpret the vital fatigue of a drowsy driver sign as yawning. Therefore, yawning detection for preventing drowsy drivers’ imprudent can be developed using computer vision. This method is easy to implement and does not affect the driver when handling a vehicle. The research aimed to detect drowsy drivers based on facial expression changes of yawning by combining the Haar Cascade classifier and a modified pre-trained model, MobileNetV2 and ResNet50. Both proposed models accurately detected real-time images using a camera. The analysis showed that the yawning detection model based on the ResNet50 algorithm is more reliable, with the model obtaining 99% of accuracy. Furthermore, ResNet50 demonstrated reproducible outcomes for yawning detection, considering having good training capabilities and overall evaluation results.
Incorporating AI Tool Along with Traditional Method for Speaking Assessment Liya Umaroh; Mukaromah Mukaromah; Muhammad Naufal; Ardiawan Bagus Harisa
INTERACTION: Jurnal Pendidikan Bahasa Vol 10 No 2 (2023): INTERACTION: Jurnal Pendidikan Bahasa
Publisher : Universitas Pendidikan Muhammadiyah (UNIMUDA) Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36232/jurnalpendidikanbahasa.v10i2.4894

Abstract

This work focused on incorporating AI tool with traditional method for speaking assessment. The descriptive qualitative has been implemented to complete this research. Problem encountered during English pronunciation was failing to distinguish between short vowel and long vowel. By employing traditional and AI tool, students got numerous benefits. They may enjoy learning with the flexibility of time and they also can engage face to face interaction while using traditional method furthermore, it is essential to acknowledge AI tool with the limitation and drawbacks. AI tool do not give the same stage of personal interconnection and on-going response as a human facilitator.
Co-Authors Dega Surono Wibowo Harisa, Ardiawan Bagus Hepatika Zidny Ilmadina Liya Umaroh MUKAROMAH MUKAROMAH