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Soft Set Theory Based Decision Support System for Mining Electronic Government Dataset
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Author(s): Deden Witarsyah (Telkom University, Bandung, Indonesia), Mohd Farhan Md Fudzee (Universiti Tun Hussein Onn Malaysia, Johor, Malaysia), Mohamad Aizi Salamat (Universiti Tun Hussein Onn Malaysia, Johor, Malaysia), Iwan Tri Riyadi Yanto (Ahmad Dahlan University, Yogyakarta, Indonesia)and Jemal Abawajy (Deakin University, Victoria, Australia)
Copyright: 2020
Volume: 16
Issue: 1
Pages: 24
Source title:
International Journal of Data Warehousing and Mining (IJDWM)
Editor(s)-in-Chief: Eric Pardede (La Trobe University, Australia)and Kiki Adhinugraha (La Trobe University, Australia)
DOI: 10.4018/IJDWM.2020010103
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Abstract
Electronic 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.
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