Analisis Penilaian Supplier Telur Bebek Menggunakan Metode Analytical Hierarchy Process (AHP) dan Data Envelopment Analysis (DEA) pada UKM Telur Asin Norce
DOI:
https://doi.org/10.71282/jurmie.v2i9.897Keywords:
Supplier Selection, Analytical Hierarchy Process (AHP), Data Envelopment Analysis (DEA), Efficiency, Criteria.Abstract
Supplier assessment is an important aspect of the supply chain that directly impacts product quality, cost efficiency, and customer satisfaction. UKM Telur Asin Noerce is a processed poultry product that is in high demand in Indonesia, so the availability of duck eggs as raw materials must be guaranteed on an ongoing basis. In the case of UKM Telur Asin Noerce, the assessment of duck egg suppliers is a strategic factor because it directly affects the quality, quantity, and smoothness of production. The problem that arises is how to determine the most efficient supplier that meets the company's criteria. This study uses a combination of the Analytical Hierarchy Process (AHP) and Data Envelopment Analysis (DEA) methods. The results identified 8 main criteria and 27 sub-criteria. The DEA method was applied to measure the relative efficiency level of each supplier based on predetermined inputs and outputs. Data was obtained through interviews with the company and quantitative data collection from duck egg suppliers. The AHP analysis results showed that quality was the criterion with the highest weight, followed by supply continuity and timeliness. Furthermore, the results of processing with the DEA-CCR model showed that of the four suppliers analyzed, there were 4 efficient suppliers with an efficiency score of 1 (100%). Based on the results of the study, using the AHP method, the Customer Care criterion had the highest weight (0.244), indicating that responsive service was a high priority. Furthermore, using the DEA super efficiency method, the results show that of the four suppliers, Demak ranks first as the priority supplier. The combination of AHP and DEA has proven to be effective in providing objective and systematic recommendations in supplier selection. Thus, companies can make more accurate and data-driven decisions.
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