The Extended Kalman Filter Method for Covid-19 Spread Prediction in Indonesia and East Java Helisyah Nur Fadhilah, Amalia Nur Alifah, Vessa Rizky Oktavia
Institut Teknologi Telkom Surabaya, Surabaya, Indonesia
Institut Teknologi Telkom Surabaya, Surabaya, Indonesia
Institut Teknologi Telkom Surabaya, Surabaya, Indonesia
Abstract
The COVID-19 pandemic has caused significant loss of human life worldwide and presented unprecedented challenges to public health, food systems, work, and many other sectors. In this paper, we make short-term predictions beyond the actual data we have using the Extended Kalman Filter (EKF) method. Basically EKF has 2 stages in estimating, the prediction stage and the correction stage. To get short term prediction results, in this paper we make modifications at the correction stage. The COVID-19 mathematical model used in this paper is the SIRD model to see the effect of mobility restriction programs on infection cases. The simulation outcomes demonstrate that mobility restriction programs in Indonesia and East Java can lower infections.
