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Supply chain efficiency transformation: analysis of raw material staff selection based on preference selection index

Amrullah, AmrullahIdaman, AkbarAl-Khowarizmi, Al-Khowarizmi
IAES International Journal of Artificial Intelligence (IJ-AI) (Sinta 1)Vol. 0 No. 01 Juni 2025
DOI10.11591/ijai.v14.i3.pp2459-2470

Abstrak

In the era of intense business globalization, supply chain management is becoming a vital key to improving the efficiency and competitiveness of enterprises. The selection of raw material supply staff is an important aspect of supply chain management, affecting smooth supply, efficiency and cost control. This research focuses on using the preference selection index (PSI) method in the selection of raw material supply staff. PSI is a tool that integrates data from multiple criteria in the selection process. The results show that PSI provides an effective evaluation in staff selection, identifies key variables that affect selection success and analyzes the impact of using PSI on supply chain efficiency and company productivity. This research fills the knowledge gap in the application of PSI in the context of raw material supply staff selection and contributes to the understanding of efficient and sustainable supply chain management. The results provide valuable insights for industries and organizations that depend on reliable raw material supply and demonstrate the potential to improve the overall staff selection process. The outcome of this study found that Muliyono received a PSI score of 0.9643 and was ranked first, while Ramli received a PSI score of 0.9548 and was ranked second.

Kata Kunci

Accuracy analysisDecision support systemMulti-criteria decision makingPreference selection indexRaw material staff selectionSupply chain efficiency transformation

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Supply chain efficiency transformation: analysis of raw material staff selection based on preference selection index | IAES International Journal of Artificial Intelligence (IJ-AI) | Publiora