This study aims to design an information visualization application that can display prospective student data and its distribution using descriptive statistical methods to assist the head of the student admission department in obtaining visualization of those two data. The Waterfall model is used for developing the app, and the descriptive statistical method for processing the data. The application can help the Head of the Student Admission Department in displaying a visualization of prospective student data and which is used as material for marketing strategies, follow-up evaluations, and report generation. The student admission data processed in this study is only in 2021 and 2022. The result of the study will fasten up decision-making in the Student Admission department. As for the university, this will show the outcome of the marketing strategy that has been conducted. The results of this data visualization help bridge the gap between the university's Board of Directors and the head of the student admissions department regarding data processing issues so that they can more accurately determine marketing strategies in the coming year. This study also can be conducted in another university with the same problem.
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