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dc.contributor.authorPuspitorini, Pipit Sari
dc.contributor.authorEffendy, Very
dc.date.accessioned2014-07-03T03:26:58Z
dc.date.available2014-07-03T03:26:58Z
dc.date.issued2014-03-27
dc.identifier.citationAksoy, Asl dan Nursel Ozturk, (2011) Supplier and performance evaluation in just in time production environment, International journal of expert system with application 38, 63516359. Amid A., Ghodyspour S.H., and O’Brien C., (2010), A Weighted max-min model for fuzzy multi objective Supplier selection in supply chain, International journal Product Economics Buyukoztan, G. And Cifci G, (2011), A Novel fuzzy multicriteria decision framework for sustainable supplier selection with incomplete information, Computer in industry. 62. 164- 174 Chou. S.Y and Chang Y.H. (2008). A decision support system for supplier selection based on a strategy aligned fuzzy SMART approach. International journal of expert system with application 34, 2241-2253 Dunteman, G.H. (1989), Principle Component Analysis Series Quantitative application in the Social Sciences. Newbury Park: Sage Publications, Inc. Ha S.H & Krishna, R (2008), A Hybrid approach to supplier selection for the maintenance of a competitive supply chain, International journal of expert system with application 34, 13031311 Lam, KC, T.S. Hu, S.T. Ng, (2005), Using the principal component analysis method as a tool in contractor pre-qualification, Construction Management and Economics. 23, 673–684. Liu, H.T and Wang, W.K., (2009), An integrated fuzzy approach for provider evaluation and selection in third party logistic, Expert System with Applications 36, 4387-4398 Subhash Sharma, (1996), Applied Multivaried Technique John Willey & Sons, Inc Smith, L.I (2002) A Tutorial Component Analysis Suhartini, (2009), Pendekatan Fuzzy Quality Function Deployment dan Goal Programming dalam Pemilihan Supplier, Tesis Fakultas Teknologi Industri Jurusan Teknik Industri, Institut Sepuluh November Surabaya. Ustun Oand Aktar Demirtas. E (2008), An integrated multi objective decision making process for multi period lot sizing with supplier selection. Omega 36 (4), 509-521 Wu, D.D., Zang Y, Wu, D and Olson. D.L. (2010), Fuzzy multi objective programming for selection and risk modelling a possibility approch. Europe Journal of Operation Research. 200, 774-787 Zadeh, L.A. (1965), Fuzzy sets. Information and Control 8, 338-353. Zeydan M., Colpan C., and Cobaglu C. (2011), A Combined methodology for supplier selection and performance. International journal of expert system with application 38, 2741-2751.en_US
dc.identifier.issn2337-4349
dc.identifier.urihttp://hdl.handle.net/11617/4510
dc.description.abstractSelection Supplier is Multi Criteria Decision Problem (MCDP) which is one of the main key in maximizing the total value for sustainable company. The study present at the construction company Indonesia. The product of construction company is box culvert . This study models the integration of fuzzy method and Principal Component Analysis (PCA). The objective of the research is to determine the best model of suppliers selection on based five criteria’s such as quality, performance, flexibility, relationship and cost. Fuzzy method is used to deal the vagueness of subjective judgements and finding criteria weight and then PCA utilize data reducing, eliminating multicollinearity among them and ranks suppliers. The suppliers of cement, gravels 10/20, gravels 5/10, sands and iron are considered in this study. For solving the problem, this study uses software statistiXL. The results show that the suppliers can be classified based on Principle Components (PCs). The best suppliers for PC1 is sands (s9, score 0.890, criietria C), PC2 is gravels 10/20 (s7, score 0.634 criietria R). The first two PC(z1 and z2) are PC1= 0.131Q+0.218F+0.758P+0.821R+0.914CdanPC2=(-0.931)Q-0.043F-0.382P+ .304R+0.188Cen_US
dc.publisherUniversitas Muhammadiyah Surakartaen_US
dc.subjectCriteriaen_US
dc.subjectFuzzyen_US
dc.subjectMulti Supplieren_US
dc.subjectPrincipal Component Analysis and Raw materialen_US
dc.titleSuppliers Selection Model Using Fuzzy Principal Component Analysisen_US
dc.typeArticleen_US


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