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AHP adalah a mathematical technique used for multi-criteria decision-making. In a way it is better than other multi-criteria techniques, as it is designed to incorporate tangible as well as non-tangible factors especially where the subjective judgments of different individuals constitute an important part of decision making (Saaty, 1980). Apart from other facts, this is rooted in the special structure of the AHP, which follows the intuitive way in which managers solve problems, and in its easy handling compared with other multi criteria decision-making procedures. Hence the intuitively solved decision problems can now be solved as procedure-orientated using AHP. The use of AHP leads to both, more transparency of the quality of management decisions and an increase in the importance of AHP (Ossadnik W& Lange O, 1999).Because of its intuitive appeal and flexibility, many corporations and governments routinely use AHP for making major policy decisions. Applications of AHP can be seen in a wide range of areas like merit salary recommendation system (Troutt M D & Tadisina S K, 1992), environmental impact assessment (Ramanathan R, 2001), credit evaluation of the manufacturing firms (Yurdakula M & Tansel Y, 2003), indoor environment assessment (Chianga CM & Laib CM, 2002), selection of alternative transportation options (Yedla S & Shrestha RM, 2003), performance measurement system (Suwignjo P et al, 2000), TQM implementation (Chin K S et al, 2002), evaluation of highway transportation (Weiwu W & Jun K, 1994), determination of key capabilities of a firm (Hafeez K et al, 2002) and for evaluation of an AHP software (Ossadnik W & Lange O, 1999) itself.AHP uses a five-step process to solve decision problems. They are
• Create a decision hierarchy by breaking down the problem into a hierarchy of decision elements.
• Collect input by a pair wise comparison of decision elements.
• Determine whether the input data satisfies a consistency test. If it does not, go back to Step 2 and redo the pair wise comparisons.
• Calculate the relative weights of the decision elements.
• Aggregate the relative weights to obtain scores and hence rankings for the decision alternatives.
One of the major reasons for the popularity of AHP is that the decision maker does not require advanced knowledge of either mathematics or decision analysis to perform first two steps (Karapetrovic S & Rosen bloom ES, 1999). Last three steps are computational and can be performed manually or using software such as Expert Choice. However, the first two are the steps where the decision maker is very much involved in the model. On the basis of the decision maker's understanding of the problem, the hierarchy can be designed and pair wise comparisons can be made of the decision elements. AHP uses redundant judgments for checking consistency, and this can exponentially increase the number of judgments to be drawn out from decision makers
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