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Evolution of the Intellectual Property Information System at the Kalimantan Institute of Technology Using the Waterfall Method and Design Thinking Rajab, Nur Ali; Marianta, Arwin; Lestari , Ika; Azhar, Nur Fajri; Prihasto, Bima
Sebatik Vol. 29 No. 2 (2025): December 2025
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v29i2.2681

Abstract

Intellectual Property (IP) Management at the Kalimantan Institute of Technology (ITK) was previously hindered by manual processes using Google Forms and Excel that were inefficient and prone to errors, and by limited information systems. This research aims to evolve the ITK Intellectual Property Information System (SIM KI) to enhance data management efficiency at the backend and improve functionality and user experience at the frontend. The development methodology uses a structured Waterfall approach. The backend is developed with Node.js (Express) and PostgreSQL, while the frontend uses React JS with interface design based on Design Thinking. System verification is conducted comprehensively through Black Box Testing, White Box Testing, User Acceptance Testing (UAT), and the System Usability Scale (SUS). The evolution results show successful system implementation that now supports four types of IP (Copyright, Patent, Trademark, Industrial Design). Backend testing through unit testing validates the reliability of internal logic, while frontend testing demonstrates functional success (Black Box), good usability (SUS score 77.89), and significant user acceptance improvement (UAT score increased from 68% to 76%). The evolution of SIM KI successfully resulted in a more efficient, functional, and well-received digital platform, which implies increased effectiveness of IP management in the academic environment of ITK.
Pengembangan Sistem Anti-Spoofing Berbasis Face Recognition Menggunakan Arsitektur YOLOv8n Tanujaya, Carmelita Angeline; Azhar, Nur Fajri; Nugroho, Bowo
Journal of Applied Computer Science and Technology Vol. 6 No. 2 (2025): Desember 2025
Publisher : Indonesian Society of Applied Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/jacost.v6i2.1362

Abstract

Face spoofing poses a major threat to facial recognition–based authentication systems, especially in web-based environments that require lightweight and real-time verification. This study develops a real-time anti-spoofing system that integrates YOLOv8n for classifying four facial categories (real, printed, digital, and mask), combined with blink-based liveness verification using the Eye Aspect Ratio (EAR). Using 400,800 images and 18 videos, two training strategies—pretrained and from scratch—were evaluated. The pretrained model achieved a precision of 99.5%, recall of 98.6%, mAP50 of 99.4%, and mAP50–95 of 90.4%, slightly outperforming the from-scratch model. EAR threshold evaluation showed that a value of 0.17 yielded the best performance with 99.02% accuracy, 100% recall, a FAR of 16.11%, and an FRR of 0%. The proposed integration of YOLOv8n and EAR represents a practical novelty for lightweight, web-based anti-spoofing, providing fast inference and stable real-time performance suitable for modern facial authentication systems.