Selection of the Best Newspaper Forecasting Method Using Holt-Winters and Long Short-Term Memory Method
Amanda Syifa Ariqoh, Josyika Nisfullaili, Nawang Putri Salsabila, Dana Prianjani, Wahyudi Sutopo, Yuniaristanto Yuniaristanto · 2023
As a result of digitalization, demand for newspapers has become more volatile and difficult to predict.This research aims to determine the best forecasting method with the smallest error value to reduce the company's rate of newspaper returns and losses.The holt-winter and long-short term memory approaches are used to analyze the data.In addition, the results of this research's forecasts were compared to the previous research that used the ARIMA method and trend line analysis method.The forecasting method will be chosen based on the lowest Mean Absolute Percentage Error (MAPE) criteria.According to this research and the previous research, the MAPE value for the trend line analysis method is 2.94%, 3.52% for the ARIMA method, 3.87% for long short-term memory; meanwhile, the holt-winter has the lowest error rate, with a MAPE value of 2%.In conclusion, the best forecasting method for forecasting newspaper demand at PT. XYZ is the holt-winter method.