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All Journal Journal of Computer Science and Informatics Engineering JITCoS : Journal of Information Technology and Computer System
Riansyah, Rusma
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Computer Science & IT Control & Systems Engineering

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Design of a Web Tracer Study Application and Alumni Data Management at the Faculty of Sharia and Law Riansyah, Rusma; Syahputra, Alwi
Journal of Computer Science and Informatics Engineering Vol 4 No 4 (2025): October
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v4i4.1145

Abstract

This research aims to design a web-based tracer study application and alumni data management system at the Faculty of Sharia and Law UINSU using the Waterfall method with a Model-View-Controller (MVC) approach. The system was developed using PHP 8.0, MySQL 8.0, HTML5, and CSS3 technologies. Functional testing shows 100% success on all features, usability evaluation using System Usability Scale (SUS) resulted in an average score of 82 (Excellent category), and performance testing shows login response time of 1.5 seconds with stability at 25 simultaneous users. User Acceptance Test shows 100% of users stated the system is easy to use. Implementation resulted in an alumni response rate of 78.6%, with 64.4% of alumni working in the legal sector and 75.4% stating that lecture competencies match work requirements. Innovative features include automatic email reminders, LinkedIn integration, dynamic visualization, and automatic password reset. The system has proven effective in improving the efficiency of alumni data collection from manual to digital and supporting data-based accreditation processes and curriculum evaluation
Implementation of a Favorite Course Search System Based on Students’ Average Grades Using the A* Algorithm Amsyah, Dwiky Oldi; Riansyah, Rusma; Aptanta, Dimas Aqila; Fachrezi, Muhammad Randy; Firdaus, Nasywa Roudhotul
JITCoS : Journal of Information Technology and Computer System Vol. 1 No. 2 (2025): Volume 1 Number 2, December 2025
Publisher : CV. Multimedia Teknologi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65230/jitcos.v1i2.50

Abstract

Optimal selection of elective courses plays an important role in supporting students’ academic success and ensuring alignment between learning interests and final project preparation. This study aims to develop a favorite course search system based on the A-Star (A*) algorithm by utilizing students’ average grades as the main evaluation variable. The system was implemented using the Java NetBeans platform, supported by datasets consisting of course names, credit weights (SKS), and grade distributions. The A* algorithm was adapted through the integration of heuristic components, including Standard Deviation and Relative Credit Load, to improve accuracy in identifying optimal course recommendations. Experimental results demonstrate that the system is capable of generating recommendations with an accuracy rate of 95%, verified through comparison between system outputs and manual calculations. The results also show that the Mitigation course ranked highest with a score of 6.1, indicating strong student performance in that subject. Overall, the system provides a practical and efficient solution for academic decision-making, enabling students to select elective courses more strategically based on data-driven insights. This study contributes to the development of computational methods in educational recommendation systems and opens opportunities for further enhancement through integration with real academic databases.
Co-Authors Amsyah, Dwiky Oldi Aptanta, Dimas Aqila Fachrezi, Muhammad Randy Firdaus, Nasywa Roudhotul Syahputra, Alwi