dc.contributor.author	Bakri Nasution, Feldiansyah
dc.date.accessioned	2024-01-15T03:36:02Z
dc.date.available	2024-01-15T03:36:02Z
dc.date.issued	2019
dc.description	Thesis (PhD. (Computer Science))
dc.description.abstract	Public policy is the critical key of the welfare programs. An Integrated Double Loop Data Driven Model is proposed to assist in Public Policymaking in solving public problems in a holistic and complete way. The Integrated Model consists of two components: Data Driven Model and Double Loop Model. The first model utilizes Big Data in E-Government Maturity (EM) for Public Policymaking (PP), in which a new E-Government Maturity Model is proposed to support data driven public policymaking based on Big Data. Subsequently, the second model adopts the double loop learning in System Dynamics (SD) whereby, a case study is discussed to show on how to utilize Big Data and System Dynamics for Public Policymaking. The interaction between Big Data, System Dynamics and Public Policymaking are captured in one conceptual model. A new method, System Breakdown Structure (SBS), to bridge between the two models is introduced in the case study. PLS-SEM test on the relationship between EM, SD and PP supports the positive correlation between EM to SD, SD to PP and EM to PP. The R square of PP is 0.48 indicating a high confidence level of the contribution of EM and SD in PP. The R square of SD is 0.45. Both results are also emphasized by the path coefficient result, whereby the path coefficient between EM to SD and SD to PP is higher than 50%. By comparing the path coefficient of EM to PP with and without the SD, the strong influence of SD puts it as full mediation effect. This result would also be similar if the multi-group analysis were conducted. Only for certain paths, there are significant statistical differences between each group; however they still produce positive correlations. The paths are EM to SD path in multigroup analysis of PNS (civil servant) and non-PNS (non-civil servant) and EM to PP path in multigroup analysis of Java and Sumatera islands (more developed region) and Other islands (less developed region). Based on the case study and PLS-SEM test, the Integrated Double Loop Data Driven Model is recommended to be implemented to assist in solving public problem.
dc.description.sponsorship	Faculty of Engineering - School of Computing
dc.identifier.uri	http://openscience.utm.my/handle/123456789/955
dc.language.iso	en
dc.publisher	Universiti Teknologi Malaysia
dc.subject	Policy sciences—Data processing
dc.subject	Policy sciences—Research
dc.subject	Dynamics—Computer programs
dc.title	Integrated double loop data driven model for public policymaking
dc.type	Thesis
dc.type	Dataset

Integrated double loop data driven model for public policymaking

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