Analysis and Design of an Expert System to Diagnose High Blood Pressure Using the Backward Chaining Method
Year: 2025
Type: article
Abstract: Hypertension, commonly known as a "silent killer," requires early detection and accurate diagnosis to prevent serious complications. This is especially crucial in primary healthcare facilities like Puskesmas Abab in Penukal Abab Lematang Ilir (PALI), where access to specialists is limited. This research developed a web-based expert system for hypertension diagnosis using the backward chaining method. The goal was to expedite medical decision-making, enhance efficiency, and improve diagnostic accuracy. Using a qualitative prototyping methodology (involving observation, literature reviews, and interviews with healthcare professionals), the system was designed with a user interface, a knowledge base, and an explanation module. Testing results showed that the system accurately diagnoses hypertension based on symptoms, aligning very well with actual medical evaluations. This confirms the effectiveness of the backward chaining method in increasing diagnostic speed and accuracy. The system also has the potential for further development to include other diseases and integrate with national health information systems
Authors: Fendri Martadinata, Arif Fadillah, Dendra
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4414650291