The Implementation and Testing of Online Self-Diagnose Covid19 Application Using CBR and UAT

I Putu Agus Eka Pratama (Department of Information Technology, Faculty of Engineering, Udayana University, Jimbaran, Bali, Indonesia)

International Journal of Advances in Data and Information Systems
Vol. 2 No. 2 (2021): October 2021 - International Journal of Advances in Data and Information System

Nowadays, at Bali Province (Indonesia), one of the public services that are still lacking related to the Covid19 pandemic is online self-diagnosis, so there are still many people who do not know whether they are exposed or not, based on general symptoms, unusual symptoms, or serious symptoms so that they can be treated immediately. In this research, Covid19CBR as a prototype of an online Covid19 self-diagnose application using the CBR (Case-Based Reasoning) method was developed, which can be run online via a web browser. Users simply input their personal data, choose the symptoms experienced or felt, then the system will provide diagnostic results online. This research use Design Science Research Methodology (DSRM) with the case study qualitative research methods, literature study data collection methods, with prototype design using Use Case Diagrams and Sequence Diagrams. The application was tested using User Acceptance Testing (UAT) with the results of 95% that mean user can use this application easily.