DEMAND FORECASTING AND AGGREGATE PLANNING STARTEGY AT PT LABITTA BENDERANG USAHA

• Main Author: Kharisma Nurfatimah, Andi
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/39246
• Institution: Institut Teknologi Bandung

PT Labitta Benderang Usaha or called PT LBU is a medium and large company provided varied shoes and sandals. PT LBU often experiences over-production and production shortages on one of the brands, Lamonty. In forecasting its demand, PT LBU only uses one method, namely the naive approach that uses the demand data of the previous month to determine the amount of production in the following month. To deal with high predicted demand, PT LBU uses a strategy to increase the number of working hours. But with this strategy, the company continues to experience production shortages in certain months. PT LBU only uses this strategy to its aggregate planning. However, the company is required to meet customer demand and to increase efficiency, especially in the production sector. To achieve this level of efficiency, companies need to find the most optimal demand forecasting method and the most appropriate aggregate planning strategy to implement. The aims of this research are to identify the most optimal demand forecasting method and the most appropriate aggregate planning to be implemented in PT LBU focusing on Lamonty Brand. Forecasting is a prediction about what will happen in the future. Forecasting methods used in this research are time-series forecasting method that using Simple Moving Average (SMA), simple exponential smoothing, Holt's model, and Winter's model. The results of these methods will be compared with the 4 errors formulas including Mean Squared Error (SME), Mean Absolute Deviation (MAD), and Mean Absolute Percentage Error (MAPE). To find which method that have the smallest forecasting error. From the error evaluation, the Winter’s Model has the smallest MAD, MSE, MAPE which is 105.33, and 21813.9, and 4.72% compared to the other methods which are company method that have 164.47 of MAD, 46,195 of MSE, and 6.66% of MAPE, 6-month moving average with 199.76 of MAD, 57568 of MSE, and 14.44% of MAPE, single exponential smoothing with 182.21 of MAD, 55912 of MSE, and 12.74% of MAPE, and Holt’s Model with MAD 105.33, MSE 55140, and MAPE 4.72%. It means that Winter’s model is the most optimal demand forecasting method to PT LBU use in Lamonty brand. From the forecasting result, it can be used to calculate the most appropriate aggregate planning strategy for the company. Aggregate planning aims to fulfill the demand by maximizing profits for the company by identifying operational parameters for a specified period of time. There are 4 strategies of aggregate planning that was practiced, which are company strategy using overtime workers, chase strategy, level strategy, and linear programming. Linear programming strategy has the smallest production cost which is IDR 463,092,586. This strategy can minimize the total cost from the strategy that the company already used up to IDR 169,147,414. So, the most appropriate aggregate planning strategy for Lamonty Brand in PT LBU is using linear programming strategy. Recommendation for Lamonty brand in PT LBU based on the research outcome is to implement the Winter’s Model to the demand forecasting method since the method has the smallest error measurement. With Winter’s model, company can minimize the error between production and demand every month to avoid over-production and production shortages. The recommendation for the aggregate strategy that PT LBU can use in Lamonty brand is optimization using linear programming strategy.