ANALYSIS OF THE EFFECTIVENESS OF DEMAND DATA PATTERNS AND LOTTING TECHNIQUES BASED ON EXPERIMENTAL DESIGN - Evan Nugraha; Rini Mulyani Sari (Universitas KH. Abdul Chalim Mojokerto, 2025)
Lot sizing technique is a method of determining the size of a lot in a procurement process. Lot sizing technique has been extensively analyzed by experts, as ordering costs, holding costs, and lot sizes have a significant impact on the total ordering cost. One of the many lot sizing techniques is the Groff algorithm, which is rarely used. Other lot sizing techniques include the Wagner-Whitin algorithm, Silver-Meal algorithm, Least Unit Cost, Least Total Cost, Part Period Balancing, Period Order Quantity, and Lot for Lot. Simulation data was collected from a real company, including ordering and holding costs, and demand data was generated with four different demand patterns: increasing, decreasing, random, and stationary. The initial analysis concludes that the Silver-Meal algorithm and Groff algorithm have relative biases that are close to the Wagner-Whitin algorithm. The second analysis concludes that for lot sizing techniques, the calculated F-value (84.3) is larger than the table F-value (2,1), indicating a significant influence of lot sizing techniques on the relative bias percentage. Furthermore, the analysis of demand patterns shows that the calculated F-value (80.0) is larger than the table F-value (2,6), indicating a significant influence of demand patterns on the relative bias percentage.