Expert System for Diagnosing Gout and Cholesterol Using Forward Chaining Method

Abstract

This study aims to address challenges in gout and cholesterol diagnostic services at Puskesmas Elly Oyu, South Jayapura, which faces significant working time and patient limitations. With only 4 medical personnel, this study proposes the use of forward chaining methods in expert systems to improve the quality of diagnosis at an affordable cost. This method allows combining factors and evidence with appropriate levels of confidence, managing uncertainty in medical diagnoses. Observations and projections show an increase in the number of patients, and with forward chaining methods, diagnosis becomes more accurate, providing a solid basis for effective intervention planning, especially in the elderly group. Furthermore, this study designed a website-based system to detect early symptoms of early childhood delay in the disease. This approach aims to ease awareness of the importance of 4 healthy 5 perfect and prevent delays in diagnosis. Waterfall development and structured design methods are used to build systems with structured stages of analysis, design, coding, and testing. Using the blackbox test method, the sustainability of the system's functionality is emphasized without regard to the details of the internal implementation. This development is expected to provide an efficient, accurate, and affordable solution in diagnosing gout and cholesterol at the Elly Oyu Health Center.