Pembuatan Sistem Tracer Study Menggunakan Metode Lean Software Development untuk Meningkatkan Efisiensi Proses Pengumpulan Data

Aulia, Salman Fariz
Subagio, Ridho Taufiq
Supriyadi, Agung

Jurnal Ilmiah Teknik Informatika dan Komunikasi
Vol. 5 No. 3 (2025): November: Jurnal Ilmiah Teknik Informatika dan Komunikasi

Catur Insan Cendekia University (UCIC) currently utilizes manual processes involving Google Forms and Excel for tracer study implementation, resulting in inefficient alumni data collection and processing characterized by error susceptibility and fragmentation. The existing alumni portal further fails to deliver value-added resources—such as statistical tracer study analytics or structured alumni databases—impeding curriculum evaluation and evidence-based decision-making. This research develops a web-based tracer study system employing Lean Software Development (LSD) methodology to enhance data management efficiency and accuracy. The technical architecture incorporates Laravel framework (PHP), MySQL database management, and Visual Studio Code. System design utilizes UML diagrams—including use case, activity, sequence, and class diagrams—to ensure functional alignment with stakeholder requirements. Blackbox testing validation confirms optimal performance of core functionalities: user authentication, questionnaire completion, alumni data administration, and tracer study monitoring across predefined scenarios. The system successfully replaces manual workflows, mitigates data loss risks, and streamlines alumni status tracking with improved questionnaire response rates. Consequently, this solution demonstrates viability for implementing structured and integrated tracer study processes at UCIC. System design utilizes Unified Modeling Language (UML) diagrams—including use case, activity, sequence, and class diagrams—to ensure functional alignment with stakeholder requirements. These diagrams guide the development team in creating an intuitive and user-friendly interface, ensuring that all stakeholders—such as alumni, administrative staff, and faculty—are able to easily interact with the system and access relevant data. Blackbox testing validation confirms optimal performance of core functionalities: user authentication, questionnaire completion, alumni data administration, and tracer study monitoring across predefined scenarios. The system's rigorous testing process also includes stress tests to ensure it can handle large volumes of data without performance degradation.