Responsive Web Application Development for Analysis of Disease Symptoms to Predict Initial Morbidity Decision Tree

Abstract

The objectives of this research are: 1) to analyze, design and develop a responsive web application for analysis of disease symptoms to predict initial morbidity decision tree, and 2) to determine the effectiveness of the development of a responsive web application for analysis of disease symptoms to predict initial morbidity decision tree. Data used in the experiment are data on illnesses, and the risk of disease. The research tools consisted of experimental tool and data collecting tool. Experimental tool is a responsive web application for analysis of disease symptoms to predict initial morbidity decision tree developed with PHP, Java Script, HTML, CSS, Bootstrap, connecting to MySQL database. Data collecting tool is system efficiency evaluation form. Research methodology can be classified into 5 steps: 1) problem and requirement analysis, 2) system design, 3) system development, 4) system testing, and 5) system evaluation by three purposively selected experts. The findings from this research are: 1) responsive web application for analysis of disease symptoms to predict initial morbidity decision tree can be performed well, can check for early symptoms of the disease and see details of influenza Dengue fever and COVID-19, and 2) the efficiency of the proposed system evaluated by three experts is in highest level (X =4.54, S.D.=0.53).