Based on various reports of COVID-19 caused by a coronavirus, this disease causes numerous problems. There are many factors that can contribute to the rapid spread of COVID-19. In this study, multi-model application is used to identify the association among various variables that cause COVID-19. The use of programmes, artificial intelligence and input data that will be processed as a symptom of the COVID-19 disease, whose data processing uses a multi-model that will classify the variables causing COVID-19. The output data will be presented in a tabular form, so that the readers can easily understand the results. The best result obtained by this programme has an accuracy of 0.979767 using a decision tree with 0.3 of the total dataset as the test data. It is expected that the rate of spread of COVID-19 can be suppressed by detecting the disease using artificial intelligence. In the future, it is expected that a multidisciplinary collaboration between medical science and mathematics can be established with the help of this programme. This enables the authenticity of the research, and the model’s performance be tested based on appropriate data in the field.
|Journal||Communications in Mathematical Biology and Neuroscience|
|Publication status||Published - 2021|
- Multi model