Implementation of a Web-Based Rule-Based System for Determining Goat Health Status from Clinical Symptoms and Feeding Patterns

Abstract

Goat farmers frequently rely on direct observation and personal experience to assess animal health, while similar clinical signs and limited access to veterinary personnel can delay initial handling. This study develops a web-based expert system using a rule-based system and forward chaining to determine goat health status from clinical symptoms, feeding patterns, and additional observable conditions. Knowledge was represented as 45 IF–THEN rules stored in a MySQL database. The application was implemented with PHP and provides modules for consultation, health-status recommendations, administration of symptoms, feeding patterns, additional conditions, health categories, diagnostic rules, and diagnosis history. The inference process begins with facts selected by the user and matches them against the knowledge base until a conclusion is obtained. The system generates four health-status outcomes: healthy, unhealthy, sick, and indicated mild illness, together with initial handling recommendations. Black-box testing covered the public interface, consultation form, forward-chaining process, result page, and administrator functions. All tested functions produced the expected outputs. The implementation demonstrates that integrating clinical signs and feeding behavior within a transparent rule-based workflow can support structured initial health assessment for goats. The system is intended as decision support and does not replace examination by a veterinarian.