The rapid development of communication and information technology has given birth to new digital-based media that have changed people's behavior in consuming mass media. Consumers are significantly moving from conventional media to digital. Print media lost readers drastically, especially from the young group. This had some negative effects on the demand for printed newspapers, with frequent supply-demand inaccuracies resulting in many newspapers being returned. For this reason, it is necessary to determine the method of forecasting the number of newspaper requests that has the smallest error rate so that it can help companies reduce losses due to newspaper returns. This study calculates demand forecasting using the trend line analysis method in three conditions, namely when demand decreases, increases, and is seasonal. Furthermore, the three conditions are compared with the forecasting results. The selection of the forecasting method for the best conditions is done by comparing the error rate (MAPE) of each condition with the trend line analysis method, then the trend line analysis method is chosen under certain conditions with the smallest error rate. Based on the comparisons made, it can be seen that the forecasting method that has the smallest error rate is the trend line analysis method with an uptrend with a MAPE value of 4.56%. Therefore, the conditions that are suitable for using the trend analysis method are obtained, namely when demand increases or has an uptrend.