Analysis of Forecasting Ingredients Performance at PT. Jebsen Jessen Ingredients Indonesia

The research conducted by the author aims to analyze which forecasting method's most appropriate to use at PT. Jebsen Jessen Ingredients Indonesia and develop strategies that will be used to increase the effectiveness of forecasting with forecasting accuracy of 60% (KPI).The research method used by the author to develop and find information to achieve goals are quantitative, descriptive and qualitative research methods.The data used by the author consists of the demand variables for raw ingredients, with the data indicators representing the demand requirements for the previous 36 months.The sampling's non-probability purposive sampling.The population utilized comprises historical raw ingredient data from Jebsen Jessen, while the forecast data samples used consist of sales for raw materials derived from ABC Analysis, totaling 18 items from January to December 2022.The results of research conducted using two forecasting methods,exponential smoothing and moving average, indicate thatMAPE value obtained through the exponential smoothing forecasting method for silicon dioxide standard grade (Japan) is 0.045 with an ɑlpha value of 0.897.Meanwhile, MAPE obtained through using moving average forecasting method for silicon dioxide standard grade (Japan) is 0.297.The relevant method for forecasting at PT. Jebsen Jessen Ingredients Indonesia is Exponential Smoothing.