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Among the responsibilities of Human Resource Department is selecting the right people for the available job. This task tends to be the most challenging due to necessity to make tough decisions under uncertainty. To minimize error occurrences and complexity of the selection process, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is adopted together with fuzzy TOPSIS and Fuzzy set theory to provide solutions to Multi-criteria decision making (MCDM) problems associated with human resource selection (HRS) process. The proposed framework of Integrated Decision Support System for Human Resource Selection using TOPSIS based models was constructed and presented in this paper.

Application of model base in group decision making that makes up a Group Decision Support System (GDSS) is of paramount importance. Analytic Hierarchy Process (AHP) is the multi-criteria decision making (MCDM) that has been applied in GDSS. In order to be effectively used in GDSS, AHP needs to be customized so that it is more user friendly with ease of used features. In this paper, we propose an enhanced AHP model for GDSS tendering. The enhanced AHP method used is the Guided Ranked AHP (GRAHP). It is a technique where decision matrix tables are automatically filled in based on ranked data. However, the generated values in the decision matrix tables can still be altered by following the guidelines which in turn serve the purpose of improving the consistency of the decision matrix table. This process is transparent to Decision Makers because the degree of data inconsistency is visible. A prototype system based on tendering process has been developed to test the GRAHP model in terms of its applicability and robustness.

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The objective ofthis paper is to describe aframework of and propose a framework for improving the existing single Decision Support System (DSS) for a tendering process. There are criteria decision model (i.e. statistical model). The proposed some public agencies that still perform a decision analysis based on model is an integration of statistical, weight, and Guided single criteria. One agency, Jabatan Kerja Raya Malaysia (JKRM) Analytic Hierarchy Process (GAHP) model AHP was is using a statistical model in performing its tendering process. In this paper, Multi Criteria Decision Making (MSCDaMty) model is iod by T MasMLSatyoin1990 Iisa multi-attribute proposed by integrating the existing statistical models with weight, decision making (MCDM) methodology for choosing the and Guided Analytic Hierarchy Process (GAHP). The framework best among a set of alternatives via pair comparison process. consists of a series of steps beginning with determining whether GAHP is our propose term for AHP data entry matrices tenderers fulfil the prerequisites. Those who pass the first stage will articulated with a systematic guidance for a decision maker proceed to the second stage evaluation. The second stage is to (DM) to enter data into the system. This new approach could determine the Cut-offPrice (COP), andfreak prices using statistical reduce the possibility of inconsistency with data entry to the methods. The third and final stage is a true DSS where a decision AHP matrices. maker (DM) can evaluate the criteria, and alternatives using The project framework consists of a series of steps weight model, and GAHP. The contribution of this research lies in the methodology for integrating statistical, weight, and GAHP begin withs. detrin whether te fil th models in order to perform tendering analysis as to achieve the final prerequisites. Those who pass the first stage will proceed to ranking of contractors for JKRM tendering in association with a the second stage evaluation. The second stage is to determine system developed by the authors. The system integrates a systematic the Cut-off Price (COP), and freak prices using statistical guidance for AHP data entry matrices for which we coin the term methods. The final stage is where a DM can evaluate the GAHP meant to minimize possibility of inconsistency data entry alternatives using GAHP. selected by a DM.The study aims to achieve the following objectives:

The increase in student enrolment into institution of higher learning, and the great increase in flexibility in choice of courses has made examination scheduling very difficult to handle in the traditional scheduling system. This paper investigates a quadratic assignment approach in examination scheduling by presenting a quadratic assignment approach to eliminate or reduce the level of conflicts in the examination timetabling. The examination with the highest number of students will be prioritized across all faculty courses, followed by other criteria such as courses with the highest number of students from different faculties. A framework for optimizing and handling the conflicts at all constraint levels is proposed to solve the examination scheduling problem.

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