Forecasting Carbon Emissions Using the SARIMA and LSTM Methods - Syifa Ilma Nabila Suwandi; Raras Tyasnurita; Hanifan Muhayat (Informatics Engineering Dept., Faculty of Engineering, University of Mataram, 2022)
The majority of greenhouse gas (GHG) effects are caused by very high levels of carbon emissions in the world. Therefore, it is necessary to take action to control the levels of carbon emissions in the world. In this study, the world's carbon emission levels were forecasted based on time series data on carbon emissions from 1949 to 2018 in North America. This study uses 2 forecasting methods, namely SARIMA and LSTM, with the consideration that both methods are considered capable of providing good results. Forecasting results show that the best parameter for SARIMA is [(0,1,0) (1,1,0)12] with a MAPE of 1.995%. Meanwhile, if you use the LSTM method with parameters 1 input, 4 hidden layers, and output 1, it produces a MAPE of 0.540%. This condition makes the LSTM method more optimal for predicting carbon emission levels in the world.