Ahmad, Fadhilah and Othman, Aida and M Saman, M Yazid and Mohamad Noor, N. M. (2007) DSS FOR TENDERING PROCESS : INTEGRATING STATISTICAL SINGLE-CRITERIA MODEL WITH MCDM MODELS. In: The 7th IEEE International Symposium on Signal Processing and Information Technology, 15-18 December 2007, Cairo, Egypt.

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The objective of this paper is to describe a framework of Decision Support System (DSS) for a tendering process. There are some public agencies that still perform a decision analysis based on single criteria. One agency, Jabatan Kerja Raya Malaysia (JKRM) is using a statistical model in performing its tendering process. In this paper, Multi Criteria Decision Making (MCDM) model is proposed by integrating the existing statistical models with weights, and Guided Analytic Hierarchy Process (GAHP) models. The framework consists of a series of steps beginning with determining whether the tenderers fulfil the precondition requirements. Those who passed the first stage will proceed to the second stage evaluation. The second stage is to determine the Cut Off Price (COP), and freak prices using statistical methods. The final stage is a true DSS where a decision maker (DM) can evaluate the alternatives using GAHP. The contribution of this research lies in the methodology for integrating statistical, weight, and GAHP model in order to perform tendering analysis as to achieve the most recommended final ranking of contractors for JKRM tendering in association with a system developed by the authors. The system integrates a systematic guidance for AHP data entry matrices which we coin the term GAHP meant to minimize the possibility of inconsistency data entry selected by a DM.

Item Type: Conference or Workshop Item (Speech)
Keywords: DSS, MCDM, AHP, Statistical models, JKR Malaysia
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty / Institute: Faculty of Informatics & Computing
Depositing User: PM Dr. Fadhilah Ahmad
Date Deposited: 04 Sep 2014 02:49
Last Modified: 04 Sep 2014 02:49
URI: http://erep.unisza.edu.my/id/eprint/1195

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