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All Journal TEKNIK INFORMATIKA Jurnal Simetris CESS (Journal of Computer Engineering, System and Science) Network Engineering Research Operation [NERO] JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Adimas : Jurnal Pengabdian Kepada Masyarakat KOMPUTEK bit-Tech Jurnal Tecnoscienza Journal of Computer Networks, Architecture and High Performance Computing Bhakti Nagori (Jurnal Pengabdian kepada Masyarakat) Jurnal ilmiah teknologi informasi Asia Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika Mathematics, Informatics, Knowledge, And Information Research
Prasetyo, Angga
Program Studi Teknik Informatika, Fakultas Teknik, Universitas Muhammadiyah Ponorogo
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Social Sciences Other

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Journal : mathematics informatics knowledge and information research

 1 
Student Engagement Detection Based on Visual Behavior Indicators Using YOLOv8 on a Public Classroom Dataset Mohammad Bhanu Setyawan; Angga Prasetyo; Fauzan Masykur
MIKIR : Mathematics, Informatics, Knowledge And Information Research Vol. 2 No. 2 (2026): JUNE
Publisher : PT Mekar Research and Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65475/sser8h18

Abstract

Student engagement is an important indicator for evaluating the quality of the learning process; however, its measurement in conventional classrooms still largely relies on subjective and labor-intensive manual observation. This study aims to establish a reproducible baseline for student engagement detection based on visual behavioral indicators using the YOLOv8 model on a public dataset. The working dataset was constructed from two subsets of the Student Class Behavior (SCB) Dataset and restructured into five behavioral classes: hand_raising, reading, writing, bowing_head, and turn_head, resulting in 9,274 image-label pairs split into 6,491 training, 1,854 validation, and 929 test samples. The experiment used YOLOv8n with an image size of 416, a batch size of 8, and 50 effective epochs in Google Colab. Performance was evaluated using precision, recall, mAP@0.5, and mAP@0.5:0.95. The results show that the model achieved a precision of 0.4429, a recall of 0.5393, mAP@0.5 of 0.4630, and mAP@0.5:0.95 of 0.3211. The best class-level performance was observed for writing (AP 0.635) and hand_raising (AP 0.597), while bowing_head (AP 0.288) and turn_head (AP 0.332) remained comparatively weak. These findings indicate that YOLOv8n is feasible as a reproducible baseline for visual student behavior detection, although annotation refinement, comparative experiments, and architectural optimization are still required to strengthen the scientific contribution and the feasibility of real-world classroom deployment
Design and Development of a Website to Assess Students’ Good Deeds Using a Rule-Based Algorithm: A Case Study of Poncol State Vocational High School. Krisna Nurhuda; Angga Prasetyo; Fauzan Masykur
MIKIR : Mathematics, Informatics, Knowledge And Information Research Vol. 2 No. 2 (2026): JUNE
Publisher : PT Mekar Research and Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65475/c4k21m62

Abstract

The recording of student behavior points at Poncol State Vocational High School still relies on paper forms and separate logbooks. This manual procedure leads to delays in data verification, the risk of miscalculations, and a lack of transparency. This website stores data on students’ positive behavior digitally and centrally. To process this data, the system uses a rule-based algorithm through if-then logic. Built using the Laravel framework and MySQL, this program includes features for student activity submissions, teacher verification, and point calculations. Functional testing was conducted using the Black Box method. The test results show that every feature on the admin, teacher, and student pages functions as originally designed. This system is capable of automatically determining eligibility for Field Work Practice (PKL) and grade promotion based on minimum point thresholds. This automated procedure replaces manual record-keeping on paper summary sheets.
Co-Authors ., Sugianti Agung Nur Fachdillah Akbar Junio Pranata Akbar Junio Pranata Aliyadi Aliyadi Ardiyantoro Cahya Putra Arief Rahman Yusuf Cobantoro, Adi Fajaryanto David April Riyanto Diva Sari Eka Putri Dyah Mustikasari Fadelan Fadelan Faisal Syaikhuriza Fauzan Masykur Fredin Rimba Saputra Ida Widaningrum, Ida Indah Puji Astuti Ismail Abdurrozaq Zulkarnain Krisna Nurhuda Moh Bhanu Setyawan Moh Bhanu Setyawan Moh. Malyadi Mohammad Bhanu Setyawan Muhammad Titan Rama Adi Wijaya Risky Khoirul Muklis Setyawan, Moh Bhanu Windy Octavia Yovi Litanianda Yovi Litanida Zaidatul Chusnul Rahayu