Open AccessComparative method of moora, copras and topsis based on weighting of best worst method in supplier selection at ABC mining companies in Indonesia
Author(s) -
Ryco Puji Setyono,
Riyanarto Sarno
Publication year - 2020
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v19.i2.pp890-899
Subject(s) - topsis , weighting , ranking (information retrieval) , selection (genetic algorithm) , delphi method , delphi , computer science , operations research , quality (philosophy) , similarity (geometry) , operations management , mathematics , engineering , artificial intelligence , medicine , philosophy , epistemology , image (mathematics) , radiology , operating system
Supplier selection is essential to the business. The risks posed by suppliers will have a significant impact on the company's performance. Each business has distinct supplier features to mitigate this.These characteristics are divided into criteria in supplier selection. In this study, the criteria in supplier selection will be weighted by Best Worst Method (BWM) and comparing the three ranking methods, Complex Proportional Assessment (COPRAS), Multi-Objective Optimization berdasarkan Analisis Rasio (MOORA) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The sample in this study is an ABC manufacturing company engaged in mining from Indonesia. From the results of the study, there were 16 criteria using the Delphi Method. These criteria are divided into four main criteria, namely service, quality, cost and time. From the results of weighting BWM, the price sub criteria on cost criteria have the greatest weight for ABC companies. The results of the weighting are then carried out by supplier ranking by comparing the COPRAS, MOORA and TOPSIS approaches. In comparing these three methods, approaches are used based on accuracy and complexity. The COPRAS method has the highest accuracy and lowest complexity according to the ABC company.