Medical product sales forecasting at pharmaceutical distribution company (Case study: PT. Lenko Surya Perkasa Branch Office Sidoarjo)

The problems that occur in PT. Lenko Surya Perkasa Branch Office Sidoarjo based on sales and warehouse data for the period October 2019 - August 2020 said that the number of damaged products continued to increase, around 23% of the total product, low sales quantity, and manual restock quantity estimates that often missed, made the warehouse storage level higher so that the product damaged due to being in the warehouse for too long. Because of that, we need a system that can predict how many sold of the product as a basis for consideration restocking products to minimize the level of warehouse storage and damaged products. The results of this study said that the least square method was not suitable because the data did not have a physical meaning of a mathematical model. However, it can describe the trend of sales which in this case tends to decrease. To explain the variation of a dependent variable y as a function of x most tempting approach to the problem is to use a simple polynomial through least square with MAPE values 42,40468 and MSE 3687209.365 with the optimum orde of the polynomial is 6. The comparison method used in this study is a simple moving average using Ma (2), Ma (3), Ma (4) stated that forecast results from SMA also produce curves that are similar to the actual data. It shows that SMA is also suitable to use when the data did not have a physical meaning of a mathematical model but did not fit when there is a big enough data spike, proven by the MAPE and MSE values which are still higher than simple polynomial regression.