https://jurnal.untag-sby.ac.id/index.php/jitsc Department of Information Systems and Technology, Universitas 17 Agustus 1945 Surabaya en-US Journal of Information Technology and Cyber Security 2987-3878 <p>&nbsp;</p> <p>Copyright Notice based on COPE (Committee on Publication Ethics) for JITCS: Journal of Information Technology and Cyber Security</p> <ol> <li class="show"> <p><strong>Ownership and Copyright:</strong></p> <ol> <li class="show"><strong>JITCS</strong>: Journal of Information Technology and Cyber Security respects the intellectual property rights of authors. 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If proven, appropriate actions, including rejection of the manuscript, retraction of the published article, or other corrective measures, will be taken.</li> </ol> </li> <li class="show"> <p><strong>Open Access Licensing:</strong></p> <ol> <li class="show">JITCS supports open access publishing and encourages authors to consider publishing their work under the CC BY-NC-ND 4.0 license to promote the dissemination and use of knowledge in the field of information technology and cyber security.</li> <li class="show">The specific terms and conditions of the CC BY-NC-ND 4.0 license will be clearly indicated on the published articles.</li> </ol> </li> <li class="show"> <p><strong>Policy Review:</strong> This Copyright Notice will be periodically reviewed and updated to ensure its continued relevance and compliance with copyright laws, ethical standards, and open access principles in scholarly publishing. Any updates or revisions to the notice will be communicated to the relevant stakeholders.</p> </li> </ol> <p>By adhering to this Copyright Notice, JITCS aims to protect the rights of authors, promote proper attribution and citation practices, and facilitate the responsible and legal use of the published content in accordance with the CC BY-NC-ND 4.0 license.</p> https://jurnal.untag-sby.ac.id/index.php/jitsc/article/view/12216 <p>The increasing reliance on digital platforms for academic and governmental purposes necessitates robust cybersecurity measures. Consequently, identifying vulnerability is critical to ensuring data security and providing actionable recommendations for cybersecurity officers. Platforms like Sinta (Science and Technology Index), which focus on collecting peer-reviewed papers and maintaining researcher’s research records, represents significant governmental contributions in academia. Cybersecurity awareness is demonstrated through events organized to evaluate the vulnerability of the platform, enabling researchers to access its security and report potential issues. This study addresses these concerns by conducting system penetration testing using the OWASP and Burp Suite Framework, focusing on identifying five critical vulnerabilities. The evaluation examines issues, such as sensitive data exposure in API responses, error log disclosures, email enumeration, and improper access to system files. The results reveal that the platform suffers from multiple levels of security vulnerabilities, prompting recommendations for authorities to take actions to mitigate potential risks effectively.&nbsp;</p> Supangat Supangat Anis Rahmawati Amna Mochamad Yovi Fatchur Rochman ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc-nd/4.0 2025-03-03 2025-03-03 10.30996/jitcs.12216 https://jurnal.untag-sby.ac.id/index.php/jitsc/article/view/12278 <p>In 2020, Politeknik Perkerapian Indonesia Madiun (PPI Madiun) faced significant challenges due to the COVID-19 pandemic, which led to the implementation of both Work from Office (WFO) and Work From Home (WFH) policies. To support these policies, PPI Madiun utilized the Electronic Attendance and Remote Assignment Monitoring System (SKEMA RAJA) provided by the Indonesian Ministry of Transportation. However, this system lacked an integrated facial recognition feature to ensure the accuracy of attendance data. Facial recognition technology presents a viable solution to enhance the reliability and efficiency of this attendance system. One effective technology for face recognition is You Only Look Once version 5 (YOLOv5), which has been proven to detect objects with high speed and accuracy. This study aims to develop a face recognition system for PPI Madiun employees using YOLOv5. The results demonstrate that YOLOv5 can detect faces from multiple angles—including right, left, top, bottom, and front—with 100% accuracy under optimal conditions. Additionally, YOLOv5 successfully detects faces in real-time from varying distances (10 cm, 20 cm, and 30 cm), achieving 80% accuracy. The system's performance is influenced by factors such as the angle of capture, lighting conditions, and facial expressions.</p> Sunaryo Sunaryo Teguh Arifianto Muhammad Afif Amalul Arifidin ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc-nd/4.0 2025-03-03 2025-03-03 10.30996/jitcs.12278