In mid-April 2020, UNESCO monitored 191 countries and stated that around 1.723 trillion students in the world were affected by the policy of school from home. It is feared that school closures could hamper the provision of education services and could disrupt the education process which will affect the level of quality of education. There is still no creation of a computational model for the spread of covid as the main framework for schools reopening safely during the pandemic situation. Although there is already a framework from WHO and the government, there is no measuring tool that can evaluate the effect of reopening schools while the Covid-19 pandemic. For this reason, this research seeks to produce a model for the spread of Covid-19 as a basis for determining policies for safely reopening schools during the pandemic. In this research, we produced a recommendation to reopen face-to-face learning in the form of a dashboard. Recommendations are given by predicting the number of cases in each subdistrict using a predictive model. The prediction results are also combined with the factors that have been determined by the government to give recommendations. The allotment of recommendations process involves a critical factor analysis process where we identify which factors are dominant as a basis of a controllable pandemic.