Showing papers by "Rusli Abdullah published in 2018"

Conceptual Model Development of Big Data Analytics Implementation Assessment Effect on Decision-Making

Abstract: The significance of big data advancement has benefited various organizations to leverage the potential insights and capabilities of big data in organizational performance and decision-making. However, the analytics outcome and quality of big data analytics (BDA) implementation has yet to be addressed. Therefore the aims of this paper are to identify and analyze the affecting factors and elements of BDA implementation and to propose a conceptual model for effective decision-making through BDA implementation assessment. The model is developed based on three dimensions such as performing data strategy (organization), collaborative knowledge worker (people) and executing data analytics (technology). The findings of this ongoing study proceeds with designing a proposed conceptual model with the research hypothesis and may provide a better assessment model for effective decision-making in the long run.

Optical Character Recognition for Quranic Image Similarity Matching

Abstract: The detection and recognition and then conversion of the characters in an image into a text are called optical character recognition (OCR). A distinctive-type of OCR is used to process Arabic characters, namely, Arabic OCR. OCR is increasingly used in many applications, where this process is preferred to automatically perform a process without human association. The Quranic text contains two elements, namely, diacritics and characters. However, processing these elements may cause malfunction to the OCR system and reduce its level of accuracy. In this paper, a new method is proposed to check the similarity and originality of Quranic content. This method is based on a combination of Quranic diacritic and character recognition techniques. Diacritic detections are performed using a region-based algorithm. An optimization technique is applied to increase the recognition ratio. Moreover, character recognition is performed based on the projection method. An optimization technique is applied to increase the recognition ratio. The result of the proposed method is compared with the standard Mushaf al Madinah benchmark to find similarities that match with texts of the Holy Quran. The obtained accuracy was superior to the other tested K-nearest neighbor (knn) algorithm and published results in the literature. The accuracies were 96.4286% and 92.3077% better in the improved knn algorithm for diacritics and characters, respectively, than in the knn algorithm.

Mapping and Analyzing Process of Cloud-based Education as a Service (CEaaS) Model for Cloud Computing Adoption in Higher Education Institutions

Abstract: A newly evolved computing paradigm used to deliver everything-as-a-service (XaaS) for various business organizations is known as Cloud Computing (CC) It is used most especially by educational organizations for educational purposes anywhere and anytime via scalability and an approach that saves cost (pay-per-use) There are a number of problems faced by Higher Education Institutions (HEIs) such as the growing need of infrastructure and IT, providing good and affordable educational services, increasing of participants, increasing education quality provision Cloud Computing (CC) provides an excellent substitute for HEIs by supporting a reduction in cost, improvement in quality, through this means sustainability in education is obtained by providing good educational services Recent research patterns on CC are directly focused on the applications, benefits, costs, technology, and security of CC However, it was noticed that less empirical evidence and research focus is been given to the adoption of CC at an organization level A model is proposed with a mapping matrix of its constructs based on the four dominant theories in the field of this adopted technology, the theories are: Technology-organization-environment (TOE) theory, The Fit-Viability Model (FVM), Diffusion of Innovation (DOI) Theory, and Institutional (INT) theory Implications, potential contributions to research, and suggestions for future study are discussed

Towards developing a cloud-based education as a service (ceaas) model for cloud computing adoption in higher education institutions

Abstract: This paper attempts to provides a distinctive contribution for the body of knowledge in studying the theoriticalmodels and factors affecting cloud computing (CC) adoption in higher educa-tion institutions (HEIs) at organizational level incorporating four dominant models; Technology–organization–environment (TOE) theory, The Fit-Viability Model (FVM), Diffusion of Innova-tion (DOI) Theory, and Institutional (INT) theo-ry,to deliver cloud-based education as a service (CEaaS) in HEIs.

Information System Success and Knowledge Grid Integration in Facilitating Knowledge Sharing Among Big Data Community

Abstract: Nowadays many domains interested to use big data to improve their decision making, strategic planning, and productivity while communication infrastructure supports various applications for users to share their resources, ideas or experiences. However, accessing, managing, analyzing, and using the rapidly expanding big data had raised challenges especially because of dispersed and heterogeneous nature of data. This review aimed to identify the factors to influence facilitating knowledge sharing among big data community from user satisfaction aspect and the way knowledge grid effect big data sharing by Delone and Maclean model for information system success. The research analysis and results revealed three features of knowledge grid which may influence information and system quality which defined as main factors affect knowledge sharing among the community from member's aspect. It also demonstrates seven factors to measure the facilitating knowledge sharing from community member's satisfaction view and quantity of knowledge sharing. Finally, the review established an initial conceptual model for facilitating knowledge sharing among big data which in follow up research will review by domain experts.

Effecting factors of knowledge integration through social media in small medium enterprises environment

Abstract: Knowledge Integration (KI) has been significant concern in analyzing the organization performance. KI also has been challenged by the emergence and continued development technologies that have made new sources of information and knowledge available to Small Medium Enterprises (SMEs). Social media are widely adopted by organizations to enhance the effectiveness of KI practices. The purpose of this study to investigate the factors that influence of KI through social media. Based on the 11 selected papers, this review has established 12 factors that may influence of knowledge integration through social media. Hence, this research contribute to the practice and research of KI and social media and its effectiveness towards the organizational performance.

Expert Review on Big Data Analytics Implementation Model in Data-driven Decision-Making

Abstract: Data-driven decision-making can offer improved insights for information value and create new business opportunity The purpose of this paper is to present the findings of expert opinion in verifying the influencing factors in big data analytics (BDA) implementation that are beneficial in developing the BDA implementation assessment model The study was carried out by conducting face-to-face approach sessions with three academicians and four industry experts who have vast experience in big data research and its implementation The findings from these exercises has confirmed and verified the content of the ten factors that include organization dimension (such as big data strategy, top management support, resource commitment, organizational relationship), people dimension (such as analytics skills, managerial skills and analytics culture) and technology dimension (includes data infrastructures, information processing and quality) were appropriate for the research model It was described using descriptive analysis such as frequency, mean and standard deviation Once the verification process is complete, the research model will be validated through survey in the future work

Validation of Curriculum Design Information System Model

Abstract: Information system (IS) is important to institution of higher learning (IHL) especially in the domain of curriculum design. Without the support of IS, curriculum design in IHL is time-consuming, error-prone and much effort need to put in by curriculum designers. Although there are numerous IS developed in curriculum design domain for the past few years, there is still lack of specific IS curriculum design model found in IHL. This study aims to propose an IS model which provide guidance during curriculum design process. Model validation phase begin with development of prototype which explains the process of creating a prototype according to the proposed model. The study collected 80 responses from the survey and the study resulted that the IS model is useful and able to reduce time, error and effort during curriculum design process.

Architectural design of experience based factory model for software development process in cloud computing: integration with workflow and multi-agent system

Abstract: A model which is based on experience factory approach has been proposed earlier, called EBF-SD, to overcome the limitations of experience management in software development domain. An application prototype, which is then called SDeX, is developed based on the proposed model. The study on correlation analysis indicates that automation do have positive relationship with other components: knowledge management, cloud, collaboration and portal. This paper further discusses the high level prototype development with the emphasis on the architectural design. Automation features are incorporated in the design in which workflow system and intelligent agents are integrated, and the facilitation of cloud environment is empowered to further support the automation.

Analytical Hierarchy Process for Knowledge Integration

Abstract: This paper presents the design of analytical hierarchy process for Knowledge Integration (KI) in Small Medium Enterprises (SMEs). An Analytical Hierarchy Process (AHP) was used to assist in building the model and help draw decisions. In order to illustrate the application of AHP, there are 3 main factors and 13 sub-factors that determine the decision of tools. In this study, Expert Choice™ software is used to conduct the experimental assessments. The judgments were found to be consistent, precise and justifiable with narrow marginal consistency values.