Functional Evaluation of the Logia Dashboard Using Boundary Value Testing and Cause-Effect Graph Techniques - Muhammad Rizky Aulia Ramadhan; Friska Abadi; Dodon Turianto Nugrahadi; Setyo Wahyu Saputro; Rudy Herteno (Universitas Amikom Purwokerto, 2025)
The Logia Dashboard is a web-based information system used to manage rehabilitation plant data on post-mining land. As an alpha-stage system, Logia requires thorough functional and performance evaluation to ensure that all input validations, logical processes, and system responses operate correctly before wider implementation. This study aims to evaluate the functional reliability and performance of the Logia Dashboard by applying a combined approach of Boundary Value Testing (BVT) and Cause-Effect Graph (CEG) techniques, supported by performance testing using Google Lighthouse. The research design adopts a black-box testing approach. BVT is applied to validate input boundaries on critical features, including login, data editing, QR code generation, and account creation. Meanwhile, CEG is used to model logical relationships between input conditions and system outputs to generate systematic test cases. A total of 39 optimized functional test cases were executed in a controlled local environment. Performance testing was conducted using Lighthouse by measuring key metrics such as First Contentful Paint (FCP), Largest Contentful Paint (LCP), Total Blocking Time (TBT), and Cumulative Layout Shift (CLS). The functional testing results show that 37 out of 39 test cases passed, yielding a success rate of 94.87%. Two failed cases were identified in the login feature, indicating weaknesses in input validation feedback. Performance testing produced an average Lighthouse score of 97, demonstrating that the system has excellent load speed and interface stability, although minor layout instability was detected on certain pages. These results indicate that the combined application of BVT and CEG is effective for detecting boundary-related and logical input errors in alpha-stage web systems. The findings also provide concrete recommendations for improving login validation and interface stability, supporting further development of the Logia Dashboard toward a more reliable and robust system for post-mining land management.