The popularity of big data analytics (BDA) has boosted the interest of organisations into exploiting their large scale data. This technology can become a strategic stimulation for organisations to achieve competitive advantage and sustainable growth. Previous BDA research, however, has focused more on introducing more traits, known as Vs for big data traits, while ignoring the quality of data when examining the application of BDA. Therefore, this study aims to explore the effect of big data traits and data quality dimensions on BDA application. This study has formulated 10 hypotheses that comprised of the relationships of big data traits, accuracy, believability, completeness, timeliness, ease of operation, and BDA application constructs. This study conducted a survey using a questionnaire as a data collection instrument. Then, the partial least squares structural equation modelling technique was used to analyse the hypothesised relationships between the constructs. The findings revealed that big data traits can significantly affect all constructs for data quality dimensions and that the ease of operation construct has a significant effect on BDA application. This study contributes to the literature by bringing new insights to the field of BDA and may serve as a guideline for future researchers and practitioners when studying BDA application.

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The Euler method is a first-order numerical procedure for solving Ordinary Differential Equation (ODEs) problems. It is an effective and easy method to solve initial value problems. Although Euler provides simple procedure for solving ODEs, there have been issues such as complexity, time of processing and accuracy that compelled the use of other, more complex, methods. Improvements to the Euler method have attracted much attention resulting in numerous modified Euler methods. This paper proposes Cube Arithmetic, a modified Euler method with improved accuracy. The efficiency of Cube Arithmetic was compared with Euler Arithmetic and tested using SCILAB against exact solutions. Results indicate that not only Cube Arithmetic provided solutions that are similar to exact solutions at small step size, but also at higher step size, hence producing more accurate results.

Nowadays, stress has become the main reason to cause health problems. The human’s lifestyle has been increasing due to the fast development of technologies which help to improve performance and productivity indirectly increased the burden of human lifestyle. Many studies have done to identify the cause of stress and the effect of stress among university students. However, stress monitoring is not well mentioned in the previous works especially stress monitoring with questionnaire-based. Thus, this research tried to come out with a mobile application that fit to use to monitor the stress level by using a questionnaire. Mobile-D used to identify and develop the mobile application, namely as Stress Catcher. Mobile-D approach allows Test-driven development and it is suitable to use for mobile applications development. A prototype of Stress Catcher will function to prove the usefulness in human lifestyle.

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