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All Journal JOURNAL SCIENTIFIC OF MANDALIKA (JSM) Riwayat: Educational Journal of History and Humanities
Husnaini, Azizah Nurul
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Humanities Education Languange, Linguistic, Communication & Media Social Sciences Other

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Analysis of Vocational High School Students' Skills Through Deep Learning Husnaini, Azizah Nurul; Irianto, Tenri Ugi; Munawwar, Muhammad Subchan
Riwayat: Educational Journal of History and Humanities Vol 8, No 4 (2025): October
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jr.v8i4.49499

Abstract

This study explores the application of deep learning techniques in assessing and enhancing the skills of vocational high school (VHS) students. Vocational education plays a critical role in preparing students for the workforce, and the integration of artificial intelligence, particularly deep learning, has the potential to transform how students practical and theoretical skills are evaluated. Through a comprehensive review of existing literature, this research investigates the effectiveness of deep learning models, such as deep neural networks (DNNs) and convolutional neural networks (CNNs), in predicting and assessing vocational students' competencies. The findings reveal that deep learning offers promising accuracy in skill prediction and personalized feedback, with applications ranging from automated grading systems to skill-specific assessments in technical fields. However, challenges such as data quality, model interpretability, and integration with traditional education systems remain significant obstacles. The study concludes with recommendations for further research, including expanding deep learning applications to real-time assessments and hybrid evaluation methods. Overall, this research highlights the potential of deep learning to enhance vocational education but underscores the need for addressing existing challenges to ensure its effective implementation.
Digital Education Management in Improving the Quality of Technology-Based Learning Husnaini, Azizah Nurul; Lucio Marcal Gomes; Mashudi Rofik; Jakoep Ezra Harianto; Moch. Edy Purwanto
Journal Scientific of Mandalika (JSM) e-ISSN 2745-5955 | p-ISSN 2809-0543 Vol. 7 No. 2 (2026)
Publisher : Institut Penelitian dan Pengembangan Mandalika Indonesia (IP2MI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/10.36312/vol7iss2pp265-275

Abstract

This study aims to explore the role of Digital Education Management Systems (DEMS) in improving the quality of technology-based learning. Using a qualitative method with a library research approach, this research analyzes various theories, models, and previous studies related to the integration of technology in education management. The findings indicate that DEMS play a crucial role in enhancing educational quality by streamlining administrative tasks, facilitating personalized learning, and supporting data-driven decision-making. Additionally, digital leadership is found to be essential in ensuring the effective implementation of DEMS, fostering a culture of innovation and continuous improvement within educational institutions. However, challenges such as digital infrastructure limitations, resistance to technology adoption, and the digital divide remain barriers that must be addressed for optimal implementation. This study suggests the need for equitable access to technology and the professional development of educators and leaders to improve their digital literacy. Overall, while DEMS hold great potential to enhance technology-based learning, their successful implementation heavily depends on overcoming the existing barriers. Future research is recommended to further investigate strategies to bridge the digital divide and evaluate the long-term impact of DEMS on student learning outcomes.
Co-Authors irianto, tenri ugi Jakoep Ezra Harianto Lucio Marcal Gomes Mashudi Rofik Moch. Edy Purwanto Munawwar, Muhammad Subchan