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All Journal International Journal of Advances in Applied Sciences Jurnal Pendidikan Vokasi Jurnal Penelitian Saintek JPTK: Jurnal Pendidikan Teknologi dan Kejuruan Jurnal Sains dan Teknologi Jurnal Edukasi dan Penelitian Informatika (JEPIN) ELINVO (Electronics, Informatics, and Vocational Education) Journal of Education Technology Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Media Computer Science Jurnal Atma Inovasia International Journal of Technology and Education Research Journal of Information Engineering and Technology Journal of Information Technology and Education (JITED)
Masduki Zakarijah
Universitas Negeri Yogyakarta
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Physics Social Sciences Other

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Journal : jurnal media computer science

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A Systematic Review of Educational Facial Emotion Recognition: Datasets, Methods, Modality, and Potential Transfer to Vocational Teaching Contexts Pipit Utami; Masduki Zakarijah; Satrio Wiroyudho Pratomo; Mozan Osman Gebalr; Dwi Osman Indriyani; Bismaka Sahasika; Hanif Nurkhalis; Tomy Herlambang
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.v4i2.10588

Abstract

Facial emotion recognition (FER) has emerged as a promising component of educational technology, yet its integration into pedagogical practice remains uneven, particularly in vocational learning contexts. This systematic review examines 38 empirical studies published between 2015 and 2025, identified through a PRISMA-guided search of major academic databases, including Scopus. The synthesis explores how datasets, model architectures, multimodal learning signals, and system design shape the applicability of affect analytics in authentic instructional settings. The findings indicate that progress in educational FER is largely driven by benchmark datasets and incremental architectural refinement evaluated under controlled conditions, which limits transferability to hands-on learning environments. While lightweight, attention-enhanced models and multimodal approaches improve deployment feasibility and affective interpretation, most systems remain open-loop and rarely support sustained pedagogical adaptation. Overall, the review highlights that advancing educational FER requires closer alignment between data practices, model and modality design, and the pedagogical realities of vocational education.
IoT-Enabled Dairy Systems: From Sensing and Data Integration to Operational Evaluation Pipit Utami; Masduki Zakarijah; Mashoedah Mashoedah; Zidni Fikriawan; Nabila Yanti; Debora Aritonang; Gregoria Gendhis Pertiwi; Anafrio Rizqy Arba Pratama; Damarjati Azra
Jurnal Media Computer Science Vol 3 No 2 (2024): Juli
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v3i2.10590

Abstract

The adoption of Internet of Things (IoT) technologies in dairy farming has expanded rapidly, yet the literature remains dominated by isolated technological components rather than operationally integrated systems. This study synthesizes research on IoT-based dairy farming systems through an end-to-end system perspective linking system purposes, sensing, data integration, intelligence, operational outputs, and evaluation. A systematic literature review was conducted on 38 Scopus-indexed articles published between 2020 and 2024 following the PRISMA protocol. The synthesis indicates that IoT applications are primarily oriented toward operational performance and initial quality indicators, barn environmental monitoring, animal health and welfare management, and operational efficiency and resource management. Although sensing technologies are relatively mature at the component level, most systems remain monitoring-oriented and support decision-making mainly through notifications and early warnings, with limited automation and operational evaluation. This review contributes a system-level conceptual framework that highlights the gap between technological capability and operational readiness, guiding the development of more coherent and operationally meaningful IoT applications in dairy farming.
Co-Authors Abyansyah, Daffa Stefian Akbar Aliyavi Aljauhari, Moh Ali Anafrio Rizqy Arba Pratama Apri Nuryanto Arya Sony Bayu Nugraha, Nikko Aji Bismaka Sahasika Damarjati Azra Danar, Bartholomeus Debora Aritonang Dwi Osman Indriyani Dwi Rahdiyanta Dzul Fadli Rahman Eko Marpanaji Fardiansyah Nur Aziz Gregoria Gendhis Pertiwi Gusti, Wahyu Ramadhani Hanif Nurkhalis Ibnu Hartopo Islamy, Sofyan Mashoedah Mashoedah May Danisa Mochamad Bruri Triyono Mozan Osman Gebalr Muhammad Indra Muhammad Resa Arif Yudianto Muslikhin Nabila Yanti Nadhir Fachrul Rozam Pardjono, P. Pipit Utami Pramudi Utomo Priyanto, Priyanto Priyo Nugroho Adi Purno Tri Aji Sadewa, Arya Yudha Satrio Wiroyudho Pratomo Soenarto Soenarto Sudji Munadi Suprapto Suprapto Tika Novita Sari Tika Widari Tomy Herlambang Umi Rochayati Wahyu Ramadhani Gusti Zidni Fikriawan