Forecasting With Time Series Method at PT. RSM in Bekasi Jawa Barat

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Fanji Andi Bimantoro
Sugiyono Madelan
Ahmad Badawi Saluy


This study aims to determine the most valid forecasting method based on the time series method. This research uses a quantitative descriptive method, the research variable is sales data of MT products belonging to PT. RSM period August 2018 to January 2021. Data processing using Microsoft excel and Minitab 19 software. ABC analysis results show product codes RSM020, RSM021, and RSM017 occupy the three highest ranks in class A by contributing 26.16% sales figures. Based on the forecasting results using various time series methods (linear trend, decomposition, moving average, single exponential smoothing, Holt Method, and Winter Method) it is found that the Winter Method produces the lowest MAPE value, which is below 20%. Product code RSM020 with an alpha value of 0.06; beta 0.09; and 0.07 gamma produces 17.2% MAPE. Product code RSM021 with an alpha value of 0.01; beta 0.01; and 0.01 gamma produces a 15.3% MAPE. Product code RSM017 with an alpha value of 0.01; beta 0.02; and 0.02 gamma produces 18.1% MAPE.

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