Pemodelan Adaptive Inventory Control untuk Procurement dan Pengendalian Persediaan dengan Teknik Associative Rules pada Agroindustri Pembuatan Ban

Abstract

Current tough industrial competition has been pushing tyre industry to strengthen customer’s satisfaction and to improve production planning and inventory control (PPIC). There are so many problems found in PPIC aspect that are reflected as a consequence of stochastic lead times and stochastic changes in this aspect. By using this model, we are trying to minimize inventory without causing any harm to the industry. This concept offers a way to face the stochastic problems and to help company to deal with adaptive data .The Adaptive Inventory Control is the latest invent for production planning to replace the MRP method. Double Exponential Smoothing method is used in Adaptive Inventory Control model specifically, because this is the best method to forecast the demand of raw material. The Associative Rules is one of data mining technique that used to optimized inventory control system in production activity. The double exponential smoothing method and associative rules mining technique processed by using historical data of transaction in the warehouse. The associative rules mining is used to decide which material that should be attached with another material as one package of material. The results of this analyzed data are 14 rules that show which material bundling should be chosen to make an optimized and simplified PPIC management system. All of those result, provide a better way of PPIC system that can improve industry’s performances.