The cloud computing has been able to help users to access the data easily and effectively. However, cloud security is highly emphasized to cloud users to ensure data is securely stored. The cloud security can be handled well by chosen trusted cloud service provider in getting high impact on the cloud security. The relationship between cloud security with the provider selection is much needed to ensure the extent to which data is securely stored in a cloud. Therefore, in this paper the quantitative method was conducted to measure the correlation between the selected the right cloud service provider influence the cloud security. Thus, knowledgeable person in having the experiences in using the cloud service was taking from two institution of higher learning (IHL) as a respondent. In addition, variability and normality data analysis was firstly conducted to obtain the consistency of the data. Then, the correlation between cloud security factor and provider selection factor was conducted using spearman correlation matrix and scatter graph in identifying the closely and significant the value in influencing between the factors. Thus, the correlation relationship analysis result shown the selected the right cloud provider’s give higher impact to cloud security.

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Educational web application has become a popular platform among academicians in delivering daily routine task over the last decade. To ensure the application meets user satisfaction is not a straightforward process. A questionnaire has been used in determining the characteristics needed in web-based integrated student assessment or in short, WBISA application. Rasch Measurement Model (RMM) has also been applied in constructing the quality model of WBISA application. In the beginning, there is a need to identify and remove item misfit, person misfit which affect the model development in achieving the initial model. Furthermore, a category response from the respondents needs to be analysed to identify the pattern of responses to determine whether they follow the rules applied in the Principal Component Analysis (PCA). Seven misfit items and ten misfit persons have been removed from the final analysis which results in good and acceptable PCA value as suggested by Rasch Model. The Person reliability is 0.96 (Excellent) and item reliability is 0.88 (Good). The model error shows a value of 0.25 which is considered as very good. The PCA values increased from 34.3% to 41.9%. Using Rasch, a model with eight constructs consisting of Usability,