Decision Support System for Bank Credit Application using Simple Additive Weighting Method

Authors

  • Budiraharjo Department of informatics, Institut Teknologi Nasional (Itenas), Bandung - INDONESIA
  • Mira Musrini Department of informatics, Institut Teknologi Nasional (Itenas), Bandung - INDONESIA
  • Willy Edya Sukma Student Department of informatics, Institut Teknologi Nasional (Itenas), Bandung - INDONESIA

Keywords:

Decision Support System, Simple Additive Weighting, multicriteria decision-making, banking credit grant, eligibility rank

Abstract

Decision Support System (DSS), in general, is a system that helps the decision-making process. In most applications, DSS is used to help managers in making business decisions, to improve data processing, to speed up business process, and to improve the quality and the service of banking credit approval. This paper discusses the process of building a DSS for banking credit approval using Simple Additive Weighting (SAW). SAW, which is one of the Multi-Attribute Decision Making methods, is a multicriteria decision-making technique which emphasizes the relative importance of the corresponding criterion to generate debtor’s eligibility ranks to be used as the bases for banking credit grants. This study was conducted at Bank Perkreditan Rakyat Syariah (BPRS) Al-Salaam in Bandung.

References

Adriyendi. 2015. Multi-Attribute Decision Making Using Simple Additive Weighting and Weighted Product in Food Choice. International Journal of Information Engineering and Electronic Business, Vol. 6, pp. 8-14.

C. Ruan, and J. Yang. 2015. Hesitant Fuzzy Multi-Attribute Decision-Making Method Considering the Credibility. Journal of Computational Information Systems, Vol. 11, pp. 423-432.

Edya Sukma, Willy. 2017. Pembangunan Sistem Pendukung Keputusan Pengajuan Kredit Dengan Metode Simple Additive Weighting (SAW) (Studi Kasus : BPR Syariah). Bandung, Tugas Akhir Jurusan Teknik Informatika.

Efraim Turban; Jay E. Aronson; Ting-Peng Liang. 2008. Decision Support Systems and Intelligent Systems. New Jersey: US, Prentice Hall, Inc.

F. Burstein; C. W. Holsapple. 2008. Handbook on Decision Support Systems. Berlin: Springer Verlag.

Gachet, A. 2004. Building Model-Driven Decision Support Systems with Dicodess. Zurich, VDF.

K. S. S. Anupama, S. S. Gowri, B. P. Rao, and P. Rajesh. 2015. Application of MADM Algorithms to Network

Selection. International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering, Vol. 3, Issue 6, pp. 64-67.

Kulik, C., L. Roberson and E. Perry. 2007. The Multiple-Category Problem: Category Activation and Inhibition in the Hiring Process. Acad. Manage. Rev., Vol. 32 No. 2, pp. 529-48.

L. Abdullah and C.W. R. Adawiyah. 2014. Simple Additive Weighting Methods of Multi Criteria Decision Making and Applications: A Decade Review. International Journal of Information Processing and Management, Vol. 5, No. 1, pp. 39-49.

Triantaphyllou, E. 2000. Multi-Criteria Decision Making: A Comparative Study. Dordrecht, The Netherlands: Springer.

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Published

2017-11-01

Issue

FoITIC 2017

Section

FoITIC 2017