Inventory Replacement Decision Support System Using Clustering and Analytical Hierarchy Process (AHP) Methods

Rusli  Nurjaman; Eneng Tita Tosida; Boldson Herdianto Situmorang

doi:10.47194/ijgor.v6i4.436

Authors

Rusli Nurjaman
rusli.nurzaman@gmail.com
Eneng Tita Tosida
Boldson Herdianto Situmorang

Keywords:

Analytical Hierarchy Process (AHP), Clustering, Goods Inventory, K-Means, Decision Support System

Abstract

The Center for Human Resources Development of Transportation Apparatus (PPSDMAP) still faces obstacles in manual inventory management, resulting in a long time required to determine which items are suitable or need to be replaced. This study aims to develop a web-based Decision Support System (DSS) to assist the inventory replacement decision-making process effectively and efficiently. The K-Means Clustering method was used to group inventory data based on age, condition, and value (price) attributes using 230 inventory data from January 1–November 30, 2023. The test results produced a Davies-Bouldin Index (DBI) value of 0.435 with six optimal clusters. Furthermore, the Analytical Hierarchy Process (AHP) method was used to determine the priority of handling strategies for less suitable or unsuitable inventory groups, with a Consistency Ratio (CR) below 10%, indicating a good level of consistency. The results of the study indicate that the developed system can assist PPSDMAP in grouping inventory objectively and support inventory replacement decision-making in a systematic, efficient, and measurable manner.

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