An Application of Rough Set Theory for Clustering Performance Expectancy of Indonesian e-Government Dataset

Performance expectancy has been studied as an important factor which influences e-government. Therefore, grouping of e-government users involving performance expectancy factor is still challenging. Computational model can be explored as an efficient clustering technique for grouping e-government users. This paper presents an application of rough set theory for clustering performance expectancy of e-government user. The propose technique base on the selection of the best clustering attribute where the maximum dependency of attribute in e-government data is used. The datasets are taken from a survey aimed to understand of the adoption issue in e-government service usage at Bandung city in Indonesia. At this stage of the research, we point how a soft set approach for data clustering can be used to select the best clustering attribute. The result of this study will present useful information for decision maker in order to make policy concerning theirs people and may potentially give a recommendation how to design and develop e-government system in improving public service.