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INDONESIA
Jurnal Pendidikan, Sains dan Teknologi
Published by CV. Information Technology Training Center - Indonesia
ISSN : -     EISSN : 29635373     DOI : https://doi.org/10.47233/jpst
Core Subject : Science, Education, Social, Engineering,
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Languange, Linguistic, Communication & Media Mathematics Social Sciences
Jurnal Pendidikan, Sains dan Teknologi (E-ISSN : 2963-5373) Merupakan Jurnal Penelitian dan Kajian Ilmiah yang diterbitkan oleh CV.ITTC – INDONESIA. Redaksi menerima kiriman hasil kajian dan penelitian di bidang ilmu , Pengembangan dan implementasi model pembelajaran, Pengembangan bahan ajar, Teknologi Pembelajaran, Analisis Kebijakan Pendidikan, Pembelajaran Online, Media Pembelajaran, Strategi Pembelajaran, dan Model Pembelajaran, Matematika Terapan dalam Pendidikan dan Industri, Fisika Terapan dalam Pendidikan dan Industri, Biologi Terapan dalam Pendidikan dan Industri, Kimia Terapan dalam Pendidikan dan Industri, Teknik Elektronika, Big Data, Robotika, Teknologi Masa Depan, Kecerdasan Buatan, Teknik Elektro, Ilmu Komputer, Teknik Informatika, Teknik Telekomunikasi, Informasi, Teknologi Komunikasi, dan Teknologi Cerdas. Jurnal Pendidikan, Sains dan Teknologi terbit 2 kali dalam setahun yaitu bulan juni dan desember.
Arjuna Subject : Ilmu Sosial - Pendidikan
Articles 2 Documents
 1 
Search results for , issue "Vol. 5 No. 2 (2026): April-Juni" : 2 Documents clear
Pengaruh Penggunaan Media Sosial Tiktok Terhadap Karakter Siswa Kelas XI Di SMA Negeri 1 X Koto Singkarak chaniago, silviya; Putri, Desi Armi Eka; ., Ikhwan
Jurnal Pendidikan, Sains Dan Teknologi Vol. 5 No. 2 (2026): April-Juni
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jpst.v5i2.4589

Abstract

This research is motivated by the low character of students at SMA Negeri 1 X Koto Singkarak which is allegedly influenced by the use of TikTok social media. The purpose of the study was to determine the influence of TikTok social media use on the character of grade XI students at SMA Negeri 1 X Koto Singkarak. This type of research is descriptive with a quantitative approach. The research population is 183 students in grade XI for the 2024/2025 school year, with the cluster random sampling technique a sample of 65 people was obtained. The data analysis technique used is simple linear regression. The results of the study showed that the use of TikTok social media had a positive and significant effect on students' character with a contribution of 11.7%. The calculated t value of 2.885 is greater than the t of table 1.669 at a significance level of 0.05, so the hypothesis is accepted. Based on these results, it can be concluded that the use of TikTok social media has an influence on students' characters. The suggestion for students is to be able to manage the time of using TikTok social media so that they are more focused on learning and wiser in utilizing social media.
Sistem Absensi Real-Time Berbasis Face Recognition Menggunakan YOLOv4 Dan OpenCv Rasyid, Arief Fadhlurrahman; Fauzi, Alfharizky
Jurnal Pendidikan, Sains Dan Teknologi Vol. 5 No. 2 (2026): April-Juni
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jpst.v5i2.4611

Abstract

Digital transformation in attendance data management still faces several challenges, particularly related to low accuracy, potential fraud, and inefficiency in conventional methods such as manual signatures or ID-based systems that are vulnerable to misuse. This study aims to develop an automated attendance system based on face recognition to improve accuracy, efficiency, and reliability in real-time attendance recording. The method used in this study is a deep learning approach employing the YOLOv4 algorithm, implemented using the Python programming language and supported by the OpenCV library for digital image processing. The system is designed to detect and recognize user faces directly through a camera device. The research stages include requirement analysis, system architecture design, model development, system implementation, and performance evaluation using metrics such as precision, recall, and accuracy. The analysis technique is based on a confusion matrix to evaluate the system's ability to classify facial data accurately and consistently. The experimental results show that the system can operate in real-time with a precision of 91.81%, recall of 100%, and accuracy of 92.03%, indicating a high level of performance in face detection and recognition. In addition, the system demonstrates good stability under various lighting conditions and face positions, making it suitable for implementation in educational institutions and workplaces as a modern, secure, and efficient attendance solution.

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