StarVizAlgo: Visual Analytic Dot Mapping in Data Visualization

Big data are large or complex data sets that need to be extracted and analyzed using computers in order to determine the data patterns, trends, and relationship. It is commonly related to extract hidden knowledge behind these data sets. Data visualization can be used to portray data in graphical and dynamic manner to extract the hidden knowledge. Spatial visualization is one of the visualization to project data related to space. One of the foremost problem in the visualization is dot overlapping. Such situation distorts the true data distribution. Thus, the aim of this study is to design a new algorithm to manage dot mapping. The algorithm is to visualize non-resident student tabulation where overlapping dot are redistributed. The new algorithm called StarVizAlgo was introduced as an enhancement to visualize the plotting pattern clearly and efficiently. It provides a better understanding and easier for users to analyze data. Furthermore, StarVizAlgo able to avoid data overlapping by introducing 'star' visualization pattern. The contribution is to the research domain of non-residents students of UiTM Shah Alam, Malaysia. It was demonstration using the 2D webpage and the result indicated that the dot distribution mapping represents a better visual analytic and more significance information.