Abstract
Global warming is caused by various factors, one of them is the emission of CO2. Time series data of CO2 emission will be analyzed using moving average and exponential smoothing to forecast the CO2 emission of the period ahead. Both models provide estimates of forecasting based on the average value of the previous data and can be used for forecasting time series data containing trend component. The best models are selected based on the smallest error value based on the criteria of MAPE, MSD, and MAD
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