Implementation of the Single Moving Average Method in Forecasting Sales of Motorcycle Spare Parts - Dwika Sherliyanda; Muhammad Dedi Irawan; Adnan Buyung Nasution (Research Group of Data Engineering, Faculty of Informatics, 2025)
Sales forecasting is an important element in inventory management to ensure product availability in accordance with market demand. One method that can be used for forecasting is the Single Moving Average (SMA), which works by calculating the average sales in a certain period to identify future sales trends. This research aims to implement the SMA method in forecasting sales of motorbike spare parts in order to increase stock management efficiency and reduce the risk of excess or shortage of inventory. This research method involves collecting historical data on sales of motorbike spare parts in a certain period, which is then analyzed using the SMA method with various average period lengths to determine the best accuracy. The research results show that the SMA method can provide fairly accurate estimates of future demand patterns. With better forecasting, stores or distributors can optimize procurement strategies and reduce unnecessary carrying costs. Apart from that, implementing this method also contributes to increasing customer satisfaction because product availability can be more guaranteed. The conclusion of this research shows that the Single Moving Average method is a simple but effective forecasting technique in motorcycle spare parts inventory management. Implementation of this method can help business people make more appropriate decisions in stock planning and marketing strategies.