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All Journal Jurnal Teknik Industri Jurnal Pendidikan Vokasi Jurnal Edukasi Elektro Journal of Tropical Soils ELINVO (Electronics, Informatics, and Vocational Education) Indonesian Journal Of Civil Engineering Education JURNAL EKONOMI PENDIDIKAN DAN KEWIRAUSAHAAN Asian Journal of Agriculture Journal of Vocational Education Studies (JOVES) Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat International Journal of Engineering, Science and Information Technology Jurnal Wana Tropika Journal of Vocational and Technical Education (JVTE) Jurnal Media Computer Science Advance Sustainable Science, Engineering and Technology (ASSET) Jurnal Pendidikan Progresif Nozel : Jurnal Pendididikan Teknik Mesin Jurnal Wana Tropika Journal of Vocational and Career Education
Putu Sudira
Fakultas Teknologi Pertanian Universitas Gadjah Mada, Yogyakarta
Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Physics Social Sciences Transportation Other

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Application of Singular Value Decomposition for Image Compression of Yogyakarta Cosmological Axis in Digital Learning in Vocational Education Sahria, Yoga; Sudira, Putu; Salim, Mohamad Hidir Mhd
International Journal of Engineering, Science and Information Technology Vol 6, No 1 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i1.1732

Abstract

This study examines the application of the Singular Value Decomposition (SVD) method as a digital image compression technique on the Yogyakarta Cosmological Axis object which is used as a digital learning medium in vocational education. The background of this study is based on the need for high-quality visual media with efficient file sizes for easy storage, transmission, and access through digital-based learning systems. The study uses an experimental quantitative approach with data in the form of high-resolution digital images processed through SVD-based compression stages. The research procedure includes image transformation into matrix form, matrix decomposition using SVD, selection of a number of dominant singular values (ranks), and reconstruction of the compressed image. The research data were analyzed using image quality evaluation parameters, namely Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Compression Ratio (CR). The results show that an increase in the rank value is directly proportional to an increase in the quality of the reconstructed image, as indicated by a decrease in the MSE value and an increase in the PSNR and SSIM values. Conversely, a decrease in the rank value results in a higher compression rate but is followed by a degradation in the visual quality of the image. Experimental data also shows that most of the visual information of an image can be represented by a small number of principal singular values, thus allowing for significant file size reduction without losing the important visual structure of the image object. Visually, the compressed image at a medium rank value is still considered suitable for use as a learning medium because the main details, object contours, and visual characteristics of the Yogyakarta Cosmological Axis can still be recognized well. These findings prove that the SVD method is effective as a mathematical-based image compression technique to support the development of efficient, informative, and contextual digital learning media based on local wisdom in vocational education
AI-Based Teacher Guidance in Vocational Schools:A Systematic Review on Generative AI for Holistic Student Development and Administrative Support Dymyati, Ria; Siswantoyo , Siswantoyo; Sudira, Putu; Fadlullah, Yanuar Agung; Maulana, Muhamad Riyan; Yusuf, Arya; Syahria, Yoga
Journal of Vocational and Career Education Vol. 11 No. 2 (2026): December 2026
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jvce.v11i2.45441

Abstract

Generative artificial intelligence (GenAI) has emerged as a revolutionary technology in education, yet little is known about how GenAI can be specifically utilized to support teacher guidance and holistic student development, particularly in the context of vocational education. Evidence on how GenAI technology can enhance holistic student development in vocational schools, reduce administrative burdens, and support teacher guidance systems is explored in this systematic review. A synthesis of 45 peer-reviewed articles from the Scopus, Web of Science, and ERIC databases, published between 2020 and 2025 in accordance with PRISMA-ScR guidelines, was conducted. Five main thematic areas were identified through thematic analysis: (1) GenAI's function as a pedagogical assistant for individualized teacher support; (2) administrative automation that reduces teacher workload by thirty to forty percent; (3) natural language processing for qualitative analysis of student data; (4) comprehensive student development through career and character guidance; and (5) implementation challenges, including ethical issues, digital literacy gaps, and institutional readiness. These findings highlight GenAI's significant potential in addressing the teacher workload crisis, with approximately 40% of teachers' time spent on administrative tasks, while improving the quality of student guidance. However, its implementation still depends on resolving equity issues, developing robust institutional policies, and adopting human-centered pedagogical approaches. This review provides valuable insights for education practitioners, policymakers, and researchers seeking to implement sustainable AI-based guidance systems in vocational education. Recommendations include structured professional development programs, ethical frameworks for GenAI usage, and context-specific adaptation models for vocational schools, particularly in developing educational contexts.
Mobile microlearning with repeated short video access: Effects on vocational skill retention Sudira, Putu; Inderanata, Rochmad Novian; Widodo, Slamet; Wagiran, Wagiran; Aryani, Sendi Tiyas
Jurnal Pendidikan Vokasi Vol. 15 No. 3 (2025): November
Publisher : ADGVI & Graduate School of Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jpv.v15i3.95712

Abstract

This study examined whether mobile microlearning that enabled repeated access to short, SOP-anchored instructional videos improved vocational skill retention compared with conventional practice instruction. A quasi-experimental pretest–posttest–delayed posttest design was implemented with 80 undergraduate students in a practice-based course (experimental n = 40; control n = 40). The experimental group learned through segmented microlearning videos (2–6 minutes) aligned with procedural steps, safety checkpoints, and quality criteria, accessible via mobile devices for rewatching before and after workshop practice. The control group received conventional instruction through instructor demonstration and job-sheet guidance without structured video re-access. Data were collected using a validated SOP-aligned practical performance rubric, a procedural knowledge test, and an observation sheet documenting procedural errors and task completion time; perceived cognitive load was measured using a brief rating scale. Content validity was established through expert judgment and instrument refinement, and reliability was supported through inter-rater agreement for performance scoring and internal consistency for test and scale measures. Data were analyzed using descriptive statistics, Shapiro–Wilk normality tests, Levene’s homogeneity tests, and independent-samples t-tests to compare groups at pretest (baseline equivalence), posttest (immediate outcomes), and delayed posttest (retention outcomes). The results indicated that the experimental group achieved significantly higher delayed practical performance and procedural knowledge than the control group, with fewer procedural errors and faster completion time. These findings suggest that rewatchable SOP-based mobile microlearning can strengthen durable procedural competence in vocational practice settings. This study contributes empirical evidence to vocational education literature by demonstrating that structured, rewatchable SOP-based microlearning enhances durable procedural competence.
From Sensors to Vision: Evolving Data Modalities for Intelligent IoT Systems Irvandy, Dedy; Carlusiaputri, Hedi Agfiria; Sari, Anja Wulan; Sudira, Putu; Uami, Pipit
Jurnal Media Computer Science Vol 4 No 2 (2025): Juli
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v4i2.11168

Abstract

The rapid growth of the Internet of Things has increased the need for sensing systems capable of understanding complex environments beyond simple data collection. The integration of artificial intelligence and computer vision has driven a shift toward perception-oriented Artificial Intelligence of Things (AIoT) systems. This study systematically synthesizes research on vision-based sensing in AIoT, focusing on application domains, sensing modalities, AI methods, and computing architectures. A systematic literature review following PRISMA 2020 guidelines using Scopus identified 24 empirical studies published between 2018 and 2025. The findings show that AIoT vision systems are increasingly applied in manufacturing, agriculture, infrastructure, and surveillance, supporting real-time monitoring and decision-making. Core functions include detection, classification, segmentation, and activity recognition, enabled by deep learning and edge–cloud architectures. The results indicate a shift toward multimodal sensing and edge intelligence, highlighting a broader transition to perception-centric AIoT systems, with ongoing challenges in dataset generalization, multimodal integration, and efficient edge deployment.
Komparasi Keterserapan Kerja Lulusan SMK Kompetensi Keahlian TGB di DIY Jaya, Daniel Jesayanto; Saputra, Taufik Wisnu; Sudira, Putu; Triyono, Mochamad Bruri; Sutarto, Sutarto; Arifah, Shilmi; Rahmah, Nuur Lailatur; Yusuf, Arif Muhammad; Diella, Septarani Krista
Indonesian Journal Of Civil Engineering Education Vol 10, No 1 (2024): Indonesian Journal of Civil Engineering Education
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijcee.v10i1.94394

Abstract

Era disrupsi saat ini menuntut individu untuk memenuhi kebutuhan dunia kerja akan SDM berkualitas. SDM unggul merupakan aset utama perusahaan dan bangsa. Oleh karena itu, pembangunan ekonomi nasional harus direncanakan dengan baik untuk menyediakan lapangan pekerjaan. Indonesia menghadapi bonus demografi yang memerlukan perencanaan tepat agar menjadi keuntungan. Pemerintah mengeluarkan Inpres No. 9 Tahun 2016 tentang Revitalisasi SMK untuk menghasilkan lulusan berkompeten dan siap kerja. Penelitian ini menganalisis keterserapan kerja lulusan SMK kompetensi keahlian TGB di DIY, dengan lokasi di SMK N 2 Depok Sleman dan SMK N 2 Kota Yogyakarta. Data dikumpulkan melalui survey, observasi, wawancara, dan dokumentasi. Hasil menunjukkan lulusan TGB SMK N 2 Depok terserap di lapangan kerja sebesar 78,18% pada 2018 dan 75,38% pada 2019. Lulusan SMK N 2 Kota Yogyakarta lebih banyak melanjutkan studi dan sedikit yang berwirausaha. Tingginya persentase alumni yang tidak mengisi tracer study menyulitkan pelacakan keterserapan alumni.
KURIKULUM SMK DALAM MENGHADAPI ERA DISRUPSI TENAGA KERJA SERTA TANTANGAN DUNIA USAHA DAN DUNIA INDUSTRI Jaya, Daniel Jesayanto; Saputra, Taufik Wisnu; Sudira, Putu; Raharjo, Nuryadin Eko
Nozel : Jurnal Pendididikan Teknik Mesin Vol 7, No 2 (2025)
Publisher : Fakultas Keguruan dan Ilmu Pendidikan Universitas Sebelas Maret Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/nozel.v7i2.95237

Abstract

Tingginya Tingkat Pengangguran Terbuka (TPT) lulusan Sekolah Menengah Kejuruan (SMK) menyatakan secara langsung bahwa lulusan SMK saat ini masih belum kompeten. Ketidakkompetenan ini merujuk pada kurikulum yang masih kurang berhasil dalam menghasilkan tenaga kerja terampil yang dibutuhkan oleh Dunia Usaha dan Dunia Industri (DUDI). Era disrupsi tenaga kerja juga menjadi tantangan bagi SMK di samping masalah-masalah lainnya dan berkaitan erat dengan Revolusi Industri 4.0. Menghadapi tantangan ini SMK harus menyusun kurikulum yang tepat di era disrupsi tenaga kerja dunia usaha dan dunia industri. Kurikulum yang tepat sesuai dengan kebutuhan saat ini akan membantu lulusan SMK diterima bekerja di Dunia Usaha dan Dunia Industri.
Co-Authors Aanggraini, Yussi Abdulloh Hamid Abdurrahman, Afif Ade Dwi Putra Janata Adkha, Nur Faizal Agung B. Supangat Anggraini, Yussi Areisy, Hafiidhiya Janata Aryani, Sendi Tiyas Azwar Maas Bambang Djadmo Kertonegoro Benito Heru Purwanto Budiadi Carlusiaputri, Hedi Agfiria Choirunnisya', Lestari Rochmatun Dewi, Ayuana Kartika Didik Indradewa Diella, Septarani Krista Dymyati, Ria Ernawati, Enik Erny Poedjirahajoe Fadlullah, Yanuar Agung HAQ, RIJALUL Haryono Supriyo Hidayati, Tuti I WAYAN WINDIA Irvandy, Dedy Iskandar, Ranu Jaya, Daniel Jesayanto Kumalajati, Erlynda Lilik Sutiarso Linda Setiawati, Linda Maulana, Muhamad Riyan Mochamad Bruri Triyono Muhammad Irfan Luthfi MULYONO, NITISAPTO Mutohhari, Farid Nikodemus P.P.E. Nainiti, Nikodemus P.P.E. Nining Wahyuningrum Nopriyanti Nopriyanti Nurdianah, Evi Nurdiansyah, Ferizal Nuryadin Eko Raharjo Nuryake Fajaryati Nuur Wachid Abdul Majid Pipit Utami Pramu Pramu Priyanto Purwantono, Anung Slamet Dwi Rahmah, Nuur Lailatur Rinawan, Rangga Bayu Rochmad Novian Inderanata Sabarnudin, Sambas Sahid Susanto Salim, Mohamad Hidir Mhd Saputra, Taufik Wisnu Sari, Anja Wulan Shilmi Arifah Siswantoyo , Siswantoyo Siti Mazizatuz Zahroh Siti Nurul Aini, Siti Nurul Slamet Widodo Sumarni, Titi Sumiyati, S Sutarto Sutarto Syahria, Yoga Thomas Sukardi Uami, Pipit Umi Rochayati Wagiran Wagiran Wakijah, Siti Yoga Sahria Yowanita Dwi Irwanti Yuanto, Teguh Arik Yusuf, Arif Muhammad Yusuf, Arya Zamroni, Z.