Title
Soft Set Theory Based Decision Support System for Mining Electronic Government Dataset
Abstract
AbstractElectronic government (e-gov) is applied to support performance and create more efficient and effective public services. Grouping data in soft-set theory can be considered as a decision-making technique for determining the maturity level of e-government use. So far, the uncertainty of the data obtained through the questionnaire has not been maximally used as an appropriate reference for the government in determining the direction of future e-gov development policy. This study presents the maximum attribute relative (MAR) based on soft set theory to classify attribute options. The results show that facilitation conditions (FC) are the highest variable in influencing people to use e-government, followed by performance expectancy (PE) and system quality (SQ). The results provide useful information for decision makers to make policies about their citizens and potentially provide recommendations on how to design and develop e-government systems in improving public services.
Year
DOI
Venue
2020
10.4018/IJDWM.2020010103
Periodicals
Keywords
Field
DocType
Decision-Making, E-Govemment, Facilitation Conditions, Maximum Attribute Relative, Performance Expectancy, Soft-Set Theory, System Quality
Computer science,Soft set,Decision support system,Artificial intelligence,Machine learning,Government
Journal
Volume
Issue
ISSN
16
1
1548-3924
Citations 
PageRank 
References 
0
0.34
0
Authors
5