RANCANG BANGUN SISTEM INFORMASI REKAP DATA GANGGUAN PELANGGAN BERBASIS ARTIFICIAL INTELLIGENCE

This study aims to design and build a Customer Disruption Data Recap Information System integrated with Artificial Intelligence (AI) at PT Aplikanusa Lintasarta Padang to replace the manual recording process that is prone to delay and classification error. The system was developed using a Research and Development (R&D) approach with the Waterfall model, covering requirement analysis, system design using Unified Modeling Language (UML), coding with PHP 8.2 and the Laravel 12 framework with a MySQL database, and integration with the OpenRouter Artificial Intelligence API for automatic complaint-text classification. Testing was carried out through Alpha Testing (White Box and Black Box) and Beta Testing (expert validation based on ISO/IEC 25010 and end-user testing using the End-User Computing Satisfaction/EUCS method). The results show that Black Box testing achieved a 100% success rate, expert validation reached an average of 90.18% (very good), and user satisfaction testing reached 87.08% (very good). It is concluded that the developed system is valid, practical, and feasible for implementation to support faster, more accurate, and more structured handling of customer disruption reports at PT Aplikanusa Lintasarta Padang.