Model Transmisi Dinamis dari Covid-19 dengan Adanya Isolasi Mengggunakan Pendekatan Deep Learning

Abstract

Corona Virus (Covid-19) is a new virus that broke out in 2020. This virus is a new type of virus (SARS-CoV-2) and the disease is called Corona Virus Disease 2019 (COVID-19). The rapid spread of this virus has resulted in social and economic problems that occur almost all over the world, including in Indonesia. In Indonesia, almost all regions are affected by social and economic changes, such as the city of Medan. These changes are influenced by the pattern of interaction between individuals and the high number of population deaths due to the virus. The dynamic transmission of the spread of Corona Virus in the population consists of susceptible, infectious and indicated individuals (Covid-19). Human social contacts are very heterogeneous and groups that can predict the impact on infectious disease transmission are referred to as deterministic epidemics. Epidemiologists use deterministic models, where the presentation uses exposed, infected and recovered individuals. For dynamic transmission in the spread of Covid-19 using data from the Medan city covid-19 task force which individuals are exposed, infected, recovered and died. This research was conducted to produce a dynamic transmission model of Covid- 19 in the presence of isolation using a deep learning approach in Medan city. This research proposes a deep learning Covid-19 model named DeepCov to predict the spread of Covid-19 disease.