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Intelligent Supplier Evaluation Framework for Improving Procurement Decisions Across Manufacturing Organizations Using Multi-Criteria Analysis Aji Nurrohman; Alfry Aristo Jansen Sinlae; Fathan Mubina Dewadi Dewadi; Sitti Rachmawati Yahya
Journal of Industrial Engineering and Management Vol 1, No 4 (2023)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/jaiem.v1i4.43

Abstract

Supplier evaluation must balance commercial, operational, and capability considerations before a procurement decision is made. This study analyzes academic evaluation records for 12 suppliers serving an automotive-component factory. Seven criteria are available: price, quality, delivery, flexibility, after-sales service, production capacity, and financial stability. The study uses the supplied analytic-hierarchy-process weights to reproduce the supplier scorecard and rank alternatives through a weighted-sum calculation. Quality has the highest weight (0.25), followed by price (0.20) and delivery (0.18); these three criteria account for 0.63 of the total decision weight. The reported consistency-ratio values range from 0.028 to 0.063. Supplier H ranks first with an AHP-weighted score of 83.99, followed by Supplier F (82.89) and Supplier C (82.32); Supplier K ranks twelfth with 67.15. The source total scores are verified as weighted sums of the seven criterion scores. Although the accompanying documentation describes an AHP-TOPSIS approach, the available data does not include criterion directions, ideal solutions, distance measures, or closeness coefficients. The paper therefore reports a transparent AHP-weight ranking rather than attributing the supplied scores to TOPSIS. The contribution is a reproducible procurement review framework that links criterion priorities, supplier profiles, ranking results, and differentiated follow-up actions without making unsupported performance or causal claims