A Hybrid Method of AHP and COPRAS-G for Supplier Selection: A Case Study in Indonesian Leather Industry
- DOI
- 10.2991/978-2-38476-247-7_5How to use a DOI?
- Keywords
- supplier selection; criteria selection; AHP; COPRAS-G; Delphi
- Abstract
The aim of this research is to select suppliers using the Analytical Hierarchy Process (AHP) and Complex PRoportional Assessment of Alternatives with Gray Relations (COPRAS-G). The proposed technique for selecting criteria uses Delphi by considering objective and subjective factors. These criteria are then weighted by AHP and then used as the basis for selecting suppliers using COPRAS. The proposed model has been tested in the Indonesian leather industry for practical use. The suggested model can represent the dynamics of decision-making groups in supplier ranking. By using the selection of factors in this suggested model, decision makers can choose more wisely. The accuracy of the criteria set will determine the results of supplier selection. Therefore, to test the validity of the model, a sensitivity test to changes in parameters is used. The proposed method generates an effective outcome because it is not sensitive to parameter changes.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Agus Ristono AU - Tri Wahyuningsih AU - Gunawan Madyono Putro AU - Ismianti Ismianti PY - 2024 DA - 2024/09/04 TI - A Hybrid Method of AHP and COPRAS-G for Supplier Selection: A Case Study in Indonesian Leather Industry BT - Proceedings of the 2nd International Conference on Advance Research in Social and Economic Science (ICARSE 2023) PB - Atlantis Press SP - 37 EP - 51 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-247-7_5 DO - 10.2991/978-2-38476-247-7_5 ID - Ristono2024 ER -