Browsing by Author "LAZIM ABDULLAH"

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    DETERMINATION OF WEIGHT FOR LANDFILL-SITING CRITERIA UNDER CONFLICTING BIFUZZY PREFERENCE RELATION
    (Journal of Sustainability Science and Management, 2011) LAZIM ABDULLAH; NUR SYIBRAH NAIM; ABD FATAH WAHAB
    Selection of suitable landfill sites becomes more relevant as a community population increases. Potential landfill sites must be carefully screened to ensure the chosen site meets all engineering, geological, and regulatory criteria. However, choosing the right criteria and its contributions toward landfill-siting selection are very much conflicting notions and far from conclusive. Weights for landfill-siting criteria are seen as less tangible and may be seen differently. This paper investigates the determination of weights for ten criteria in landfill-siting problems using a conflicting preference approach. Three landfill management experts from three different municipalities in Kedah, Malaysia were interviewed to elicit conflicting judgements data over the criteria of landfill-site selection. The judgement data were aggregated using the proposed five-steps of conflicting bifuzzy preference relations. In this investigation, it is found that the criteria of Political Issues gained the highest weight followed by the criterion of Land Use. The results offer a good input to policy makers in landfill management, especially in a situation where weight-determination solutions are needed.
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    A MODIFIED ANALYTIC HIERARCHYAPPROACH IN RANKING HUMAN-CAPITAL INDICATORS
    (Journal of Sustainability Science and Management, 2012) LAZIM ABDULLAH; SUNADIA JAAFAR; CHE MOHD IMRAN CHE TAIB
    Evaluation on human-capital development and a knowledge-based economy becomes increasingly important as several approaches have been proposed. One of the popular methods in multi-criteria evaluation is the pair-wise comparison ofAnalytic Hierarchy Process (AHP). However, single evaluation in pair-wise comparison of AHP seems not very comprehensive in handling of human judgement. Therefore, this study aims to propose a modified analytical-hierarchy process by considering two-sided conflicting judgement and test the proposed approach to ranking indicators of human capital in Malaysian organisations. The theory of Conflicting Bi:fuzzy Sets (CBFS) was hybridised into AHP to form a modified version of decision-making tool that employed linguistic judgement and pair-wise comparison. The modified approach was employed to integrate the multifacets preferences offive criteria ofhuman capital in establishing the importance ofthe four identified indicators. A case study ofhuman-capital measurement is presented and the proposed model is applied to facilitate the decision-making process. Interviews with three decision-makers were administered to collect linguistic data over the comparative judgement of human-capital measures in Malaysia. The results show that succession rate oftraining programmes is the most important measurement indicator and creating result by using knowledge is the least-important measurement indicator. The overall ranking reflects the importance ofmeasurement indicators in steering Malaysia to become a worthy human-capital investment.
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    PREDICTION OF CARBON DIOXIDE EMISSIONS USING FUZZY LINEAR REGRESSION MODEL
    (Journal of Sustainability Science and Management, 2014) LAZIM ABDULLAH; NOOR DALINA KHALID
    Carbon dioxide (CO2) emissions have been continuously escalating in recent years. The escalating trend is consistent with the current economic activities and other uncertain variables such as demand and supply in businesses and energy needs. Linear model is one of the most commonly used methods to explain the relationship between CO2 emissions and the related economic variables. However, linear regression model fails to describe the relationship due to the variables’ uncertainty and vague information. As to overcome this problem, fuzzy linear regression model has been proposed in explaining the relationship. This paper aims to predict CO2 emissions using possibilistic fuzzy linear regression model by employing data from two countries. The prediction on the effciency of CO2 emissions for the United Kingdom (UK) and Malaysia was measured. The predictive models identifed population and Gross Domestic Products as the most effective predictors for the UK and Malaysia respectively. The root mean square errors of the UK and Malaysia predictive models were 2.895 and 1010.117 respectively. It shows that the CO2 emissions predictors of the UK are more effcient than Malaysia. Instead of crisp deterministic regression coeffcients, the fuzzy coeffcients with middle and spread values of fuzzy linear regression equations offer new contribution to describe the relationship between CO2 emissions and the related economic variables.