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

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.