Rancang Bangun Sistem Computer Based Test (CBT) Penerimaan Mahasiswa Baru Berbasis Web Menggunakan Metode Research And Development dengan Model Waterfall
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Ardiansyah Cahya Nugroho
*
Universitas Muhammadiyah Karanganyar, Karanganyar,
Indonesia
- Cucut Hariz Pratomo Universitas Muhammadiyah Karanganyar, Karanganyar, Indonesia (*) Corresponding Author
Abstract
The implementation of the New Student Admission (PMB) selection process requires an efficient, transparent, and effective system to support accurate decision-making. Previously, the Computer-Based Test (CBT) system used for PMB selection relied on the CodeIgniter framework, which was prone to limitations in data management flexibility, security, and scalability as the number of applicants increased. To address these challenges, this study redesigns a web-based PMB CBT system using the Laravel framework, which adopts the Model-View-Controller (MVC) architecture, and integrates a relational database MySQL to provide structured and maintainable data management. Most previous studies have primarily focused on the digitalization of examination processes, usability improvements, or basic system efficiency. The main innovation and contribution of this research is the implementation of a live score feature that ensures transparent and immediate presentation of examination results for participants. This study employs the Research and Development (R&D) method to design, develop, and evaluate the proposed system. The developed system includes several key features, such as participant management, question bank management, online examinations, automatic score calculation, and a live score feature for real-time result monitoring. Based on Black Box Testing, the system achieved a functional validity rate of 100%, indicating that all testing scenarios were successfully executed without errors. The proposed system contributes by enhancing the transparency of score calculation and utilizing a scalable technology architecture to assist the admission committee in managing large-scale applicant data efficiently.
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