Indonesia BFS Covid19 (IBC) Tracer Based on Web

In the handling of the Covid19 Pandemic in Indonesia, handling was carried out from the medical and Information Technology (IT) sides. On the IT side, information services for Covid19 and early detection of Covid19 based on web and mobile applications are provided. However, there is no Covid19 disaster mitigation education service for the public and government in the form of an online simulation of tracking Covid19. Good Covid19 disaster mitigation education will help the government and the community to be responsive to possible disasters and minimize the bad impacts that may occur. In this research proposal, a solution is proposed in the form of the Web-Based Indonesia BFS Covid19 (IBC) Tracer application. Through IBC Tracer, users will get an online simulation of tracking the route of the spread of Covid19 from one point (area) to another point (area) in Indonesia. The simulation results will be able to provide Covid19 disaster mitigation education to users, as well as assist the government in making the best decisions for handling Covid19. IBC Tracer was developed using the Breadth First Search (BFS) algorithm based on Artificial Intelligence (AI). Research uses the Design Science Research Methodology (DSRM) methodology with qualitative research methods in the form of case studies, data collection methods in the form of literature studies, testing methods on the developer side in the form of BlackBox Testing, and testing methods on the user side using User Acceptance Testing (UAT) and Technology Acceptance. Model (TAM). The research was carried out within a period of one year, so that it could be immediately used by the community and government to obtain the expected benefits.

Keywords: IBC Tracer, Indonesia, Breadth First Search (BFS), Covid19, disaster mitigation education