A Review of Data Quality Assessment: Data Quality Dimensions from User’s Perspective

High quality data is an important asset in numerous business and organizations. The quality of data, i.e., the ability of data to meet user requirement can have a tremendous impact in an organization to develop an astounding data quality satisfaction subsequently provide a better platform to achieve top service in organizations. The assessment of data quality dimensions must consider the degree to which data satisfy users’ needs. Data quality assessment although multi-dimensional but identical in most of the assessment structure. Therefore, it is important to develop an assessment of data quality dimensions specifically to measure the degree of user’s satisfaction and judgement of the data to obtain a correct interpretation of data quality assessment result. This paper proposes a conceptual framework of data quality assessment from user’s perspective that draws the assessment specifically to measure user requirements and satisfactions. This framework can be evaluated and will be used to improve and extend knowledge of relationship between data quality dimensions and its assessment from user’s perspective

Development of multi criteria tacit knowledge acquisition framework (MC-TKAF) to support talent development intervention program in a Malaysian comprehensive university

In Higher Education Institutions (HEI), the process of retaining leadership succession is critical since it has involved the process in choosing the right person. The purpose is to steer the institutions to sustain organizations’ excellence for academic leadership and management (ALM) position. Many ALM of Malaysia HEIs are struggling to find the right successor to replace their roles as they do not have yet any firm criteria in evaluating the competence among their potential successors in their home institutions. This study aims to propose a multi criteria tacit knowledge acquisition framework (MC-TKAF) for supporting talent development intervention program in Malaysia HEIs. It will be based on cognitive apprenticeship, socialization and informal learning theory which mostly used in acquiring knowledge from expertise to overcome talent bottleneck among novice. The main process of this study will use Fuzzy Delphi among ALM in Malaysian HEIsto get consensus judgement about the right indicator to evaluate tacit knowledge competence. Three phases involved are: Phase 1 is to analyze the existing Tacit Knowledge Acquisition (TKA) by finding the suitable parameters to construct intended framework, Phase 2 is to use the findings in Phase 1 in order to develop a new framework of Tacit Knowledge Acquisition Framework (TKAF) that suits with HEI environment. Finally, Phase 3 is to evaluate the practicality of Tacit Knowledge Acquisition Framework (TKAF) by using Multi Criteria Decision Making (MCDM) approach in supporting Talent Development Intervention Program. The objective of this paper is to propose the multi criteria tacit acquisition framework by using MCDM technique as a talent performance indicator. This paper basically will focus on Phase 1 of the research design. The constructed indicators in this paper could be served as a reference for the HEI industries to establish applicable talent performance indicators according to the properties of each TKA used

Information Security Culture Concept towards Information Security Compliance: A Comparison between IT and Non-IT Professionals

This paper examines the factors determining a positive Information Security Culture (ISC) concept and the influence of ISC towards ISP compliance intention (INT) between IT and non-IT professionals in Malaysian public universities. Partial least square structural equation modelling, using PLS MGA, is used to assess the measurement and structural models, and to compare the results between the two groups. Results indicate all factors have significant contribution towards ISC in both groups, with two out of seven ISC factors have significant differences. This study has revealed that although both groups have the same ISC factors, IT and non-IT professionals have significant difference in terms of believe that Top Management Commitment and Information Security Knowledge are required for implementing a positive ISC. In addition, there is a significant difference between these two groups in terms of the influence of ISC towards ISP compliance intention. ISC has less influence towards INT for Non-IT professionals compared to IT professionals within the same ISC. These empirical findings would benefit in formulating better security strategies by providing appropriate efforts for different groups of employees in the organizations. This study also provides a total cyber security solution for improving information security culture and employees’ compliance towards Information Security Policy

Comparing the Performance of Predictive Models Constructed Using the Techniques of Feed-Forword and Generalized Regression Neural Networks

Artificial Neural Network (ANNs) is an efficient machine learning method that can be used to fits model from data for prediction purposes. It is capable of modelling the class prediction as a nonlinear combination of the inputs. However, a number of factors may affect the accuracy of the model created using this approach. The choice of network type and how the network is optimally configured plays important role in the performance of a predictive model created using neural network techniques. This paper compares the accuracy of two typical neural network techniques used for creating a predictive model. The techniques are feed-forward neural network and the generalized regression networks. The model created using both techniques are evaluated for correctness. The resulting outputs show that, the Generalized Regression Neural Network (GRNN) consistently produces a more accurate result. Findings further show that, the fitting of the network predictive model using the technique of Feed-forward Neural Network (FNN) records error value of 1.086 higher than the generalized regression network

Using SAW, WPM, TOPSIS, AHP for selection of academic administrator roles in public university in Malaysia

There are certain qualities and traits needed to be qualified as an Academic Administrator. However, there is a lack of preparation to develop and prevent the loss of leadership and management skills among talented academicians. Lacking this preparation will also lead to the vacancy roles of Academic administrators without occupied. Thus, there is a requirement to have an appropriate model to measure knowledge, skills, and experience among potential academicians during the Talent Development Intervention program. This paper aims to formulate and compare the Multi-criteria Decision-Making methods using Simple Additive Weightage (SAW), Weight Preference Method (WPM), Analytical Hierarchical Priority (AHP), and Technique For Order Performance By Similarity To Ideal Solution (TOPSIS). One set of empirical studies based on the proposed multi-criteria tacit knowledge acquisition model is used to select the best candidate to fill in academic administrator roles. The solution for this case consistent for candidate UITM 1 for majority methods (WPM, AHP and TOPSIS) as the first choice

Predefined Object Reduction

Reduction techniques is still an open area to be explored in knowledge management. This paper defines algorithm known as Predefined Hybrid Reduction which generate its conditions for object co occurrences of original data then execute Hybrid Reduction data for their data to perform extractions. Predefined Hybrid Reduction give a proper solution for expansion the data set , it select significant object with high quality of informations, it delete every object not satisfies their conditions. It show appropriate relevant result. It provide better reduction without inconsistency problem unlike data comparisons. It manage the inferior object which store only significant data based on predefined confidence and predefined support for maintain the inferior object then Hybrid reduction which are dual reduction. As part of this proposal, a comparison test with Hybrid reduction. The conclusion part which shows better alternative result through our mode

Modeling of Strategic Alignment to Modify TOGAF Architecture Development Method Based on Business Strategy Model

Strategic alignment is generally seen as an important driver for optimizing business performance. Strategic alignment is aligning internal resource capabilities and external opportunities for superior performance. To realize the suitability of Business and IT strategies, a framework is needed, namely Enterprise Architecture (EA). One of the frameworks for EA is The Open Group Architecture Framework (TOGAF). TOGAF is a method for developing and managing the Enterprise Architecture life cycle called Architectural Development Method (ADM). This ADM integrates elements of the TOGAF standard in responding to the organization's business, and IT needs. In this paper, researchers will contribute to formulating a strategic alignment model to modify the existing strategic alignment in TOGAF ADM based on the business strategy model. In this business model strategy, there are two things: the analysis of business strategy choices and the Balanced Score Card (BSC) strategy map. Analysis of business strategy choices uses SWOT analysis as a business strategy determination based on internal and external business environment analysis. Second, the BSC strategy map is a process of mapping business strategies into the BSC strategy map, which includes four perspectives: financial, customer, internal business processes, and learning and growth perspectives. This model was tested at the Universitas Dinamika, and the results have a good alignment rate of 95%. For further research, this model can be tested in various organizations, such as universities and public and private organizations

Multi criteria tacit knowledge acquisition framework (MC-TKAF) using fuzzy delphi method for supporting talent development intervention program in Malaysian higher education institution

There are certain qualities and traits needed to be qualified as Academic Leader or Academic Manager. However, there is a lack of study regarding the preparation to develop and prevent the loss of these qualities and traits among the talented academicians. Lacking of this preparation will also lead to certain Academic Leadership Management roles leave vacant without being occupied. Thus, there is a requirement to have an appropriate model to measure the knowledge, skill and experience among potential academicians during Talent Development Intervention program. This paper aims to form criteria based proposed multi criteria tacit knowledge acquisition framework using fuzzy Delphi method in phase 2 of the study. Ten (10) expertise were used to form consensus finding. Result show that elements that are evaluated by the experts with rate of consensus between 50% to 90%. This finding will enable the proposed model to be evaluated using analysis software for model fitness towards tacit knowledge competence of potential Academic Leader or Academic Manager

Information Security Culture Concept towards Information Security Compliance: A Comparison between IT and Non-IT Professionals

This paper examines the factors determining a positive Information Security Culture (ISC) concept and the influence of ISC towards ISP compliance intention (INT) between IT and non-IT professionals in Malaysian public universities. Partial least square structural equation modelling, using PLS MGA, is used to assess the measurement and structural models, and to compare the results between the two groups. Results indicate all factors have significant contribution towards ISC in both groups, with two out of seven ISC factors have significant differences. This study has revealed that although both groups have the same ISC factors, IT and non-IT professionals have significant difference in terms of believe that Top Management Commitment and Information Security Knowledge are required for implementing a positive ISC. In addition, there is a significant difference between these two groups in terms of the influence of ISC towards ISP compliance intention. ISC has less influence towards INT for Non-IT professionals compared to IT professionals within the same ISC. These empirical findings would benefit in formulating better security strategies by providing appropriate efforts for different groups of employees in the organizations. This study also provides a total cyber security solution for improving information security culture and employees’ compliance towards Information Security Policy

An Alternative Algorithm for Soft Set Parameter Selection using Special Order

The outcome of the reduction of soft data is dependent on the quality and discount evidence that increases with optimization analysis. There is a set of techniques that can be used to reduce the data, but the different techniques showed different results as each technique is focused on solving a particular problem. This paper proposed a parameter reduction algorithm, known as 3C algorithm, to circumvent the false frequent object in reduction. Results indicated that the proposed algorithm is easy to implement and perform better than the state-of-the-art parameter reduction algorithm. Also, the proposed algorithm can be used as an effective alternative method for reducing parameters in order to enhance the decision making process. Comparative analysis were performed between the proposed algorithm and the state-of-the-art parameter reduction algorithm using several soft set in terms of parameter reductio