Building a mobile health application and heart diagnose to assist patients: Analysis and design

Along with the increasing number of people in Indonesia, the health becomes the main concern of the government of Indonesia. Dissemination of health information becomes a daunting task for the government. Data were collected from samples representing Indonesia, covering deaths throughout 2016, and at all deaths were verbal autopsies, according to World Health Organization guidelines in real time by doctors and trained personnel. From the data, it is seen that 10 types of diseases are the most common cause of death in Indonesia including cancer, cerebrovascular, and ischemic heart. But the information of 10 types of disease is still not common to the people of Indonesia. This research describes the design of a mobile application called “I'm CARE”. The application is based on the 10 most dangerous diseases in Indonesia, as reported by the health information media. The research method used is data collection method that includes interviews with several specialist doctors. It also uses the method of analysis and database design that includes the design of the conceptual database, logical, and physical. Then using manual interaction computer to design user interface on mobile application and some machine learning models such as Decision Tree, k = Nearest Neighbor (k-NN), Support Vector Machine (SVM), and Artificial Neural Network (ANN). The results achieved are the design of mobile-based application “I'm CARE” model as a health information media about 10 diseases dangerous in Indonesia and prediction model of heart. The conclusion is that with the design of “I'm CARE” mobile-based application model as health information media about 10 diseases dangerous disease in Indonesia and prediction model of heart hence dissemination of health information to Indonesian society can be improved and assist government in health area.