The Expert System For Diagnosing Rotavirus Infection For Babies Using Forward Chaining Method

Abstract

Forward chaining is a search method that begins by displaying convincing data or facts to reach a final conclusion. This method is applied to identify rotavirus infections in BABY to assist medical personnel and the community in early detection. The detection process, which was previously done manually, was considered inefficient in data management and did not utilize database-based digital storage technology. This study designed and developed a web-based expert system application using PHP and MySQL so that it can be easily accessed by users and related parties. Functionality testing was carried out using the black-box method on six main components, including registration, symptom data input, disease data input, rules data input, advice and solution data input, and output results. The test results showed that all system modules functioned as expected. This expert system has been proven to improve the efficiency of the early identification process for rotavirus infection, maintain data storage security and order, and facilitate digital access to information.  With the support of Forward Chaining method, this system is expected to assist the community and medical personnel in early detection and more effective initial treatment.