Abstract
The number of new students in the Faculty of Computer Engineering and Science of Universitas Dharmawangsa is fluctuating. As the number of new students fluctuates, the university should anticipate any potential weaknesses using the prognosis model to forecast the number of prospective students. An artificial neural network system with backpropagation method applied in this study was expected to solve problems in the prognosis of the number of new students. This study aimed to develop a system capable of forecasting the number of prospective students through a backpropagation algorithm of an artificial neural network program. This study employed new students from three departments in the last five years (2016-2020). The results of this study were 78 students consisting of 21 students from the Information Systems D3 Study Program, 36 students from the Information Technology Bachelor Degree, and 19 students from the Software Engineering Bachelor Degree, this study developed a web-based application capable of forecasting the number of prospective students that are likely to attend their undergraduate degree in the Faculty of Computer Engineering and Science of Universitas Dharmawangsa. The result of this study could be used as a consideration regarding the strategies for increasing the number of prospective students.
Published Version
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