Abstract
Data visualization is used to analyze the patterns and trends of data, including budget distributions, business analytics and so forth in a form of diagrams, charts, graphs and so on. In Malaysia, the budget is still in the form of a speech text and infographics. In the previous study, a treemap visualization technique is used to visualize the Malaysia budget, but it has resulted in data congestion as there are too many ministries and its programs in Malaysia. Besides, the visualization failed to compare previous and current budgets. Therefore, this study uses the circle packing technique to visualize Malaysia’s budget where it provides a more presentable and interactive way to explore the budget that can compare the current and previous budget on a single website. In order to construct this data visualization, it starts with the preparation of a JSON file to reorganize the budgets data and imported as an input file. Then, circle packing algorithm is used, which includes creating a new pack layout, followed by packing the root node by assigning coordinate x, y, and radius. Besides, it needs to pack the radius, and then set the size using two elements of an array. It follows by setting the padding and packing the array of siblings circles. Lastly, it encloses the circles to the packing. This algorithm is then integrated with JSON file and HTML to visualize it interactively on the web. This dynamic budget visualization webpage is a better option of exploration and it is beneficial to Malaysians as it helps the citizen in seeing a clearer picture of the distributions of their money. Furthermore, it is handy to understand the government future financial planning for Malaysia in an interactive way. This algorithm can be reusable to visualize any other financial data in a hierarchy structure.
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The authors would like to thank Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA for sponsoring this paper.
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Abdullah, N.A.S., Zulkeply, N., Idrus, Z. (2019). Malaysian Budget Visualization Using Circle Packing. In: Berry, M., Yap, B., Mohamed, A., Köppen, M. (eds) Soft Computing in Data Science. SCDS 2019. Communications in Computer and Information Science, vol 1100. Springer, Singapore. https://doi.org/10.1007/978-981-15-0399-3_7
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