Optimizing Nurse Knowledge Management in Healthcare Services using the Jaro-Winkler Algorithm

Abstract

Effective nurse knowledge management is essential for supporting clinical decision-making and ensuring high-quality patient care. However, hospitals often face challenges such as data duplication, information inconsistency, and inefficient data retrieval. This study explores the integration of the Jaro-Winkler algorithm into a nurse knowledge management model to enhance health services at Lamongan District Hospital. The algorithm was selected for its precision in measuring string similarity, which facilitates accurate data identification and the elimination of redundant entries. The methodology included data collection, system requirements analysis, algorithm implementation, and performance evaluation based on accuracy and retrieval speed. The findings revealed a 30% reduction in data duplication and a 40% increase in data retrieval speed. These improvements underscore the algorithm's effectiveness in optimizing knowledge management processes. The study contributes to the development of intelligent, technology-based systems that can be adopted by other healthcare institutions to improve service quality and operational efficiency.