Diabetes Diagnosis Expert System Based on Family History Analytic Hierarchy Process (AHP) Method

An expert system is a branch of artificial intelligence (AI) designed to replicate the decision-making abilities of a human expert in a specific domain. It utilizes a rule-based approach by incorporating expert knowledge and experience into a computer system, allowing non-expert users to analyze and solve complex problems efficiently. One of the critical applications of expert systems is in the healthcare sector, especially in supporting early diagnosis of chronic diseases such as Diabetes Mellitus. Diabetes Mellitus is a metabolic disorder characterized by elevated blood glucose levels caused by insufficient insulin production or the body's inability to effectively use insulin. It is classified into two main types: Type 1 Diabetes Mellitus (Insulin Dependent) and Type 2 Diabetes Mellitus (Non-Insulin Dependent). Key factors contributing to the onset of diabetes include genetic predisposition, obesity, and unhealthy lifestyle habits. To assist the public in self-diagnosing the risk of diabetes, a web-based expert system was developed using the Analytic Hierarchy Process (AHP), a structured decision-making method that helps prioritize multiple criteria. In this system, symptoms such as frequent thirst, weight loss, and family history of diabetes are assessed and weighted using AHP to determine a person's risk level. The system is implemented using PHP programming language and MySQL database. Users interact with the system by answering a set of predefined questions, and based on their responses, the system calculates and displays the diagnosis result with corresponding risk categories.This expert system aims to raise public awareness and provide an accessible tool for early detection and prevention of diabetes, especially in regions with limited access to healthcare professionals.