Prediksi Persediaan Barang Menggunakan Metode Weighted Moving Average, Exponential Smoothing dan Simple Moving Average

Abstract

Inventory of goods is one of the very important sales activities, because it indirectly has an impact on customer satisfaction, it is possible that customers will feel disappointed if the goods they are looking for are not available because the stock is out of stock, if this happens it is very possible even until the customer loses. To avoid customer disappointment and maintain stock of goods so that they are always available when needed, it is important necessary to predict the inventory of goods in this case are brown envelopes at photocopy shops and office stationery F2. To be able to predict the inventory of these goods, research is carried out so that the stock of brown envelopes can always be available. In this study, the authors conducted a research on the estimated supply of brown envelopes which until now were sought after by customers at the store where we did research, namely the F2 photocopy and office stationery shop. In calculating inventory estimates, the author uses three methods, namely Weighted Moving Average, Exponential Smoothing and Simple Moving Average. Data processing using the Python programming language with Jupyter Notebook, from the prediction results using the three methods, it can be seen that the best method for photocopy shops and office stationery F2 is using the Exponential Smoothing method with α=0.1. The author hopes that the results of this study can provide input to shop owners in making decisions when they will add stock of brown envelopes in the next period. If this can be known before the stock runs out, the shop owner will be better prepared in deciding how much stock should be prepared to meet customer needs, and it is also not excessive to provide stock because if there is too much stock and it is not sold for a very long time, it can reduce the value of an item that can cause loss.