IMPLEMENTASI ALGORITMA NAIVE BAYES PADA APLIKASI LAPORAN PENGADUAN MASYARAKAT KECAMATAN SIMPANG KANAN - Amanda Br Daulay; Antoni; Tasliyah Harmaini (PT. Hasba Edukasi Mandiri, 2025)
Fast, transparent, and responsive public services are key indicators of successful government administration. However, the management of public complaints at the subdistrict level is still largely done manually, resulting in issues with data management, priority setting, and the speed of follow-up actions. This study aims to design and implement a Web-based Public Complaint Report Priority Information System using the Naive Bayes algorithm to automatically classify report priorities into three categories: high, medium, and low. The system is developed using PHP programming language, MySQL database, and applies text preprocessing techniques (data cleaning, stopword removal, and stemming) before calculating probabilities using Naive Bayes. The development method used is the Software Development Life Cycle (SDLC) waterfall model, which includes requirements analysis, design, implementation, and testing. The implementation results show that the system can correctly classify report priorities based on the provided training data and facilitates the admin in monitoring and following up on complaints. This research is expected to provide a practical solution to improve the effectiveness of public services, particularly in Simpang Kanan Subdistrict, and can be further developed to cover a broader area.