Abstract
To increase the accuracy and the efficacy of client satisfaction degree of railway statistic information system, we give an AHP-based comprehensive assessment about satisfaction degree of information system, hoping to solve problems about evaluation difficulties of multi-index, multi-criteria and multi-level. Since the conventional AHP-based method is affected by subjective factors, we develop an enhanced AHP method to decrease limitations of conventional methods. Our method, still based on expert scoring, perform cluster analysis of scoring data, apply the clustering method of Euclid Distance with Weight to eliminate scores with the largest divergence, and utilize the AHP method and Function of Weight Average to obtain weight of evaluation index, which is useful to improve the accuracy and efficacy and can enhance effects of the more pivotal evaluation index on results. Finally, we prove its rationality and reliability in an evaluation of client satisfaction degree of railway statistic information system. DOI: http://dx.doi.org/10.11591/telkomnika.v11i10.3409
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