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All Journal Jurnal SOLMA Dinamisia: Jurnal Pengabdian Kepada Masyarakat JMM (Jurnal Masyarakat Mandiri) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal ABDINUS : Jurnal Pengabdian Nusantara Journal of Soft Computing Exploration Jurnal Ilmiah Ilmu Terapan Universitas Jambi Journal of Data Science Theory and Application Jurnal Informatika: Jurnal Pengembangan IT Journal of Applied Informatics Science
Hepatika Zidny Ilmadina
Politeknik Harapan Bersama
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Industrial & Manufacturing Engineering Social Sciences Other

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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 : 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.
A Web-Based Chatbot-Integrated Application for Skin Disease Detection Using ResNet50 Architecture Naovi Magfiroh; Ginanjar Wiro Sasmito; Hepatika Zidny Ilmadina
Journal of Applied Informatics Science Volume 1 Issue 1 (2025)
Publisher : GWS Tech Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65897/jais.v1.i1.31

Abstract

The skin is a vital human organ located on the outermost part of the body and is vulnerable to various external stimuli and diseases. The high prevalence of skin diseases in Indonesia indicates a lack of public awareness regarding skin health. This study aims to develop a web-based application capable of detecting 10 types of skin diseases quickly and accurately using the ResNet50 architecture and computer vision technology. The research stages include the creation of a Haar Cascade Classifier, developing an image classification model, model evaluation, chatbot development, system design, implementation, and application testing. The results show that the model achieved an accuracy of 90.10% on the training data and 89.06% on the validation data. The integrated chatbot also provided additional information with a response accuracy of 87.50%. System testing demonstrated good performance based on black-box testing and scored 77.625 on the System Usability Scale (SUS), which falls into the "Good" category. This application can detect early skin disease without requiring direct consultation with a doctor.
TEACHER SELF-EFFICACY AS A PREDICTOR OF DIGITAL LEARNING ADOPTION INTENTION AFTER CODING AND ARTIFICIAL INTELLIGENCE TRAINING: A CROSS-SECTIONAL STUDY OF INDONESIAN TEACHERS Widianti, Hesti; Saputra, Irfan Triadi; Yasmin, Arifia; Ilmadina, Hepatika Zidny
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 10 No. 3 (2026): Volume 10, Nomor 3, June 2026
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v10i3.57000

Abstract

Digital transformation in education demands continuous improvement of teacher competencies in coding and artificial intelligence (AI). The mechanism explaining why some trained teachers adopt digital innovations while others do not remains underexplored, particularly self-efficacy as a mediating pathway between training and adoption. This study analyzes post-training self-efficacy, its predictive effect on adoption intention, and whether digital competency mediates this relationship. A cross-sectional survey involved 62 teachers (TK/PAUD, elementary, junior high school) participating in a Coding and AI Technical Guidance (Bimtek) program organized by a Regional Education Office in Central Java, Indonesia, selected through total sampling. Three validated instruments were administered: a self-efficacy questionnaire (10 items, α = .904), an adoption intention questionnaire (8 items, α = .925), and a 15-item digital competency test. Data were analyzed using simple linear regression and the Baron and Kenny mediation procedure verified by the Sobel test, with post-hoc power computed using Cohen's f² benchmark. Technology self-efficacy was high (M = 4.11, SD = 0.56) and significantly predicted adoption intention (β = .776, R² = .602, p < .001), with achieved power exceeding .99 (f² = 1.51). Digital competency did not mediate this relationship (Sobel z = 0.408, p = .684), indicating self-efficacy operates through a direct affective-motivational pathway rather than competency accumulation. This study provides novel evidence that self-efficacy is a more proximal determinant of adoption intention than competency in short-duration training. Implications include redesigning Bimtek to target self-efficacy through mastery experiences and assessing self-efficacy as a training outcome indicator.
Co-Authors Ahmad MAULANA Anisa, Lulu Nadhiatun Ardi, Ardi Susanto Arif Hidayah Dairoh Dairoh Dega Surono Wibowo Dega Surono Wibowo Dega Surono Wibowo, Dega Surono Dyah Apriliani Dyah Apriliani Dyah Apriliani Eflita Yohana Fatkhurrozak, Faqih Ginanjar Wiro Sasmito Ginanjar Wiro Sasmito, Ginanjar Wiro Haqqani, Humam Asathin Hendrawan, Andre Budhi Hesti Widianti Hidayatullah, Muhammad Fikri Insani, Fariq Fadillah Gusti Juhrotun Nisa, Juhrotun Muhammad Naufal Naovi Magfiroh Rakhmah, Firda Aulia Risqi Dwi Saputri, Berliani Sanjaya, Firman Lukman Saptaryani, Titiek Deasy Saputra, Irfan Triadi Saputri, Berliani Risqi Dwi Sharfina Febbi Handayani Syarifudin Syarifudin Yasmin, Arifia