Optimization of Dental Clinic Selection Using Item-Based Collaborative Filtering with Pearson Correlation - Daffa Rahman; Ana Kurniawati; Dina Agusten (Universitas Islam Raden Rahmat, Malang, 2025)
The advancement of technology in the healthcare sector (e-health) has encouraged dental clinics in Bekasi City to adopt digital systems. However, many clinics have yet to take advantage of this technology. The wide variety of dental clinic options often makes it difficult for users to determine which clinic best suits their needs. This study developed a web-based recommendation system using the Item-Based Collaborative Filtering method and Pearson Correlation calculation. The system recommends clinics based on the similarity of ratings between items, calculated from users’ historical data, and generates predictions using the Weighted Sum algorithm. Recommendations are displayed in table format on the website. The system was developed using PHP and MySQL, with 20 dental clinics in Bekasi City as the research objects. It was tested using Blackbox Testing and User Acceptance Testing (UAT). The MAE evaluation result of 0.28 demonstrates the system's good prediction accuracy, and the SUS score of 80 places it in the