Design and Implementation of an Early Screening Application for Dengue Fever Patients Using Android-Based Decision Tree C4.5 Method

In Indonesia, dengue fever has been a public health problem for the past 46 years. According to the World Health Organization (WHO), in 2011, an estimated 2.5 billion people, or about 2/5 of the world population living in tropical and subtropical areas, were at great risk of being infected with dengue fever every year. This study aims to take advantage of the development of Android smartphone technology to design a system capable of screening the early stage of dengue fever with four possible classes, namely1^stDegree, 2^nd Degrees, 3^rdDegrees, and non-dengue using the C4.5 Decision Tree based on patients medical records at Hajj General Hospital (Rumah Sakit Haji), Surabaya, East Java. The initial diagnostic decision of this application was determined by ten input parameters, i.e., unstable fever, conjunctival hemorrhage, rash, headache, age, pulse pressure, nausea/vomiting, body temperature, heartburn (abdominal pain), and decreased appetite. To determine diagnosis results in this application, trees formation using the highest gain ratio for each parameter was conducted. This early screening application for dengue fever patients recorded an accuracy score of 95% out of 20 data tested. Evaluation results for this application showed some good ratings by obtaining the average value of the survey in visual design and user interaction test at 8.3 rates; functionality test 8.932; performance and stability at 9.168; and overall satisfaction test at 8.733. This application also recorded a high accuracy level and good application performance.