4 research outputs found

    Business Intelligence Healthcare Model: Getting the Right Requirements for Malaysian Rural Citizens

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    It is a big challenge for Malaysian healthcare authorities in providing services to rural communities. To meet up with the challenges, a concept called business intelligence (BI) is employed for their informed decision-making that utilizes their enormous data. However, only a few of BI initiatives have their success stories as many are still struggling to justify the investments. Among the most reason of the failures were that BI requirements were overlooked, leading to poor BI deployments. Taking rural healthcare in Malaysia as a case study, the paper attempts to model BI requirements using goal-oriented approach. Rural healthcare BI requirements were modelled two-folds: (1) decision making requirements, cantered on stakeholders; and (2) BI data requirements, focused on organizational and decisional aspects. The model can guide BI developers on the process and data needed in rural healthcare strategic decision-making. Theoretically it provides new insights and facilitates the improvement of new healthcare knowledge

    Requirement modeling for data warehouse using goal-UML approach: the case of health care

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    Decision makers use Data Warehouse (DW) for performing analysis on business information. DW development is a long term process with high risk of failure and it is difficult to estimate the future requirements for the decision-making. Further, the current DW design does not consider the early and late requirements analysis during its development, especially by using Unified Modeling Language (UML) approach. Due to this problem, it is crucial that current DW modeling approaches covered both early and late requirements analysis in the DW design. A case study was conducted on Malaysia Rural Health Care (MRH) to gather the requirements for DW design. The goal-oriented approach has been used to analyze the early requirements and later was mapped to UML approach to produce a new DW modeling called Goal-UML (G-UML). The proposed approach highlighted the mapping process of DW conceptual schema to a class diagram to produce a complete MRH-DW design. The correctness of the DW design was evaluated using expert reviews. The G-UML method can contribute to the development of DW and be a guideline to the DW developers to produce an improved DW design that meets all the user requirement

    An Enhanced Goal-Oriented Decision-Making Model for Self-Adaptive Systems

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    The thesis proposes a generic, configurable and enhanced goal-oriented decision-making model for self-adaptive software systems. The model has been designed to include feedback control loops as first class entities in the adaptation process whereby the decision-making processes can assess the impact of a previously executed decision, so that better decisions can be made in the future. Furthermore, the model provides the ability to detect and resolve conflicts amongst dependant adaptation requirements. The realization of the decision-model is extremely generic, flexible and extensible. It allows different voting algorithms to be specified for choosing a winner requirement for clusters of flexible adaptation requirements. Moreover, the implementation also allows for the specification of a wide variety of reinforcement learning algorithms to assess the impact of a previously executed decision. The implementation has been developed as a plug-in for a generic Java-based adaptation framework. It was tested using two case studies namely a News Web Application and an IP Telephony System. The aim of the conducted experiments was to assess the impact of the model on the systems goals and to determine the impact of feedback control loops as first class entities in the decision-making process. Based on the obtained results, it can be concluded that the model does improve the overall customer satisfaction level compared to a non-adaptive system. Moreover, it will be concluded that incorporating feedback loops as first class entities yields better results as compared to a decision-making model based solely on policies or goals
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