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Determining the needs of each item of a product that has many types is something that is difficult to do if done manually. If this happens it will be a problem in decision making by management. As experienced by Cileunyi Collection Store where as of October 2018 the number of goods reached 2,469 types / Stock Keeping Units. (SKU). Production staff find it difficult to analyse how much production needs of each item so influence management decision-making in determining capital decisions and storage space that must be allocated. In this study will be explained the proposed decision support system in the form software application to assist the process of grouping goods and provide recommendations for the procurement of goods based on predetermined criteria in the Cileunyi Collection Store. Two algorithmic approaches, Multiple Decision-Making Criteria (MCDM) and Fuzzy C-Mean (FCM) are used. The MCDM algorithm is used to determine the order or priority in multi-criteria analysis and the FCM algorithm is used to group with the same membership. The Main result of the research is to present that the MCDM and FCM algorithm can provide recommendations for the procurement of goods with various specified criteria. The testing results shows that both of MCDM and FCM algorithm reached 90%.

Hybrid multiple criteria decision and fuzzy c-means for procurement