DESIGN OF AN ANDROID-BASED LUNG DISEASE SCREENING EXPERT SYSTEM AND PATIENT EARLY WARNING USING THE FORWARD CHAINING METHOD AT WALUYO JATI, KRAKSAAN HOSPITAL

Abstract

This aims of study were design and create an android-based lung disease screening expert system and patient early warning using the forward chaining method at Waluyo Jati Kraksaan Hospital. This study used a mixed methods approach, namely descriptive qualitative and quantitative descriptive. In this descriptive qualitative research design used case study and the quantitative descriptive research design uses a survey. This research used the forward chaining method and model development using the Waterfall model. Based on the accuracy test table, it can be concluded that the Android-based lung disease diagnosis expert system uses the Forward chaining method. The ISO/IEC 9126 standard test uses two aspects, namely the usability aspect of 83.45% and the Functionality aspect of 85.1%. The certainly factor for the confidence value can be identified quite well. This is evidenced by the results of testing the system accuracy of 96.43%. An Android-based lung diagnostic expert system was built to provide identification conclusions in accordance with the thoughts of an expert, namely a lung specialist.