Proceedings of The 3rd International Conference on Management, Economics and Finance
Personal Protective Equipment Demand Forecasting and Inventory Management during COVID-19 Case Study: Public Hospital at Bandung, Indonesia
Nadya Christie, Mursyid Hasan Basri
Until January 2021, the number of COVID-19 in Indonesia cases is still increasing, especially in West Java. The COVID-19 hospital’s occupancy rate in West Java, especially Bandung, is around 80 percent. This makes the prediction of the hospital’s personal protective equipment (PPE) essential to accommodate the increasing demand, especially Public Hospital in Bandung, which is also a national referral for COVID-19. Lack of prediction methods leads to a shortage in PPE, affecting the hospital’s service to its patients. This study aimed to find the best forecasting method for COVID-19 patients hospitalized in Public Hospital in Bandung, determine the PPE demand, and find the hospital’s best inventory models. This study compares three methods to forecast the COVID-19 patients hospitalized in several facilities in the hospital. The methods are ARIMA (Auto-Regressive Integrated Moving Average), Single Exponential Smoothing, and Double Exponential Smoothing. The COVID-19 hospitalized patients forecast is then inputted to the PPE Calculator to be translated into PPE demand. The best method is chosen based on the forecast accuracy measurement using MAPE, RMSE, and MAD. The method with the smallest forecast accuracy value is considered as the best method. This study compares the EOQ (Economic Order Quantity) Model, Fixed-Time Period Model, and Naïve Model for the inventory model. As a result, the best method to forecast the COVID-19 patients hospitalized is using ARIMA because it has the least MAD, MAPE, and RMSE. Interestingly, the EOQ model is still the best inventory control method even during the COVID-19 pandemic because EOQ has the best AIL among all methods.
Keywords: Inventory Management, Personal Protective Equipment (PPE) Demand Forecasting, EOQ, ARIMA, COVID-19.