Web-Based Expert System for Diagnosing Disease Symptoms Caused by Prolonged Exposure to Laptop Screens Using the Certainty Factor Method

Abstract

Programmers are often faced with the pressure of completing projects within tight deadlines, whether during system development or when fixing bugs. This situation frequently leads them to work for extended periods in front of computer screens, often neglecting health considerations. Such habits can trigger various physical and mental health issues, including eye strain, muscle pain, sleep disturbances, and excessive stress. Based on these conditions, this study aims to design a web-based expert system that can detect early signs of potential health problems resulting from intensive digital device usage. The system was developed using the Laravel framework, which adopts the Model-View-Controller (MVC) architecture and supports application security. For the inference process, the Certainty Factor method was applied to calculate the confidence level of a diagnosis based on user-input symptoms. Knowledge about symptoms and diseases was obtained through consultations with experts and formulated into rules used by the system. In one of the tests, a user named Agus was diagnosed with Computer Vision Syndrome with a confidence level of 99.93%. This result demonstrates that the method effectively manages uncertainty and produces accurate decisions. In addition to providing diagnoses, the system also offers initial recommendations such as applying the 20-20-20 rule and adjusting screen positioning. Therefore, this system is considered effective as a preliminary consultation tool to help programmers recognize health issues before seeking professional medical assistance.