Sales Forecasting and Inventory Management: A Case Study of Chicken Manure Business

Abstract

This research aims to study the appropriate sales forecasting model. In order to adapt to meet customer needs in a timely and to study the appropriate order quantity for effective inventory management. Using the sales volume of chicken manure from January 2018 - December 2020 to forecast customer demand by time series technique are Seasonal Indices by Ratio to Trend Method, Seasonal Indices by Simple Average Method, Exponential Smoothing Method, Exponential Smoothing Holt Winter and consider different forecasting methods by calculation of measurement error 3 methods which are Mean Absolute Deviation (MAD), Mean Square Error (MSE), and Mean Percent Absolute Error (Mean Absolute Percentage Error, MAPE) for accurate forecasting results with minimal errors. Compare all forecasts and choose the most accurate forecasting method to use to forecast sales for the year 2021 and use the sales forecast in the year 2021 to determine the Economic Order Quantity

In the results of the study, it was found that the seasonal indices by ratio to trend method had the least measurement error of two-thirds of the forecasting method are MAD 1,203.63 and MAPE 7.71 which can be concluded that the forecasting by the seasonal indices by ratio to trend method is the least error and the most accurate. Sales Forecast in the Year 2021 have 53,280 sacks and an economic order quantity of 2,124 sacks