Purpose: Corporate Performance Evaluation Program (PROPER) has some objectives such as curbing carbon emissions. This program evaluates and assigns ratings to the companies' performance in managing environment. This study aims to (1) examine the effects of environmental performance (PROPER rating) on Carbon Emissions Disclosure (CED); and (2) identify the determinants of PROPER rating. Results: Reckoning with carbon emissions checklist from Carbon Disclosure Project (CDP), data are gathered from 144 firms. The average of CED among Indonesian manufacturing companies is still relatively low (24%). Path analysis shows that CED is influenced by PROPER rating and Board Size, but not by Leverage and Profitability. Conclusion: Board Size and Profitability are important determinants of PROPER rating, but Leverage and Company Size are not. PROPER is considered effective to improve companies' transparency in managing carbon emissions among Indonesian manufacturing companies.

<span lang="EN-US">Susceptible exposed infectious recovered (SEIR) is among the epidemiological models used in forecasting the spread of disease in large populations. SEIR is a fitting model for coronavirus disease (COVID-19) spread prediction. Somehow, in its original form, SEIR could not measure the impact of lockdowns. So, in the SEIR equations system utilized in this study, a variable was included to evaluate the impact of varying levels of social distance on the transmission of COVID-19. Additionally, we applied artificial intelligence utilizing the deep neural network machine learning (ML) technique. On the initial spread data for Saudi Arabia that were available up to June 25^th, 2021, this improved SEIR model was used. The study shows possible infection to around 3.1 million persons without lockdown in Saudi Arabia at the peak of spread, which lasts for about 3 months beginning from the lockdown date (March 21^st). On the other hand, the Kingdom's current partial lockdown policy was estimated to cut the estimated number of infections to 0.5 million over nine months. The data shows that stricter lockdowns may successfully flatten the COVID-19 graph curve in Saudi Arabia. We successfully predicted the COVID-19 epidemic's peaks and sizes using our modified deep neural network (DNN) and SEIR model.</span>