Backpropagation Model in Predicting the Location of Prospective Freshman Schools for Promotion Optimization

M. F. Rozi, Dedy Hartama, Ika Purnama Sari, Rafiqa Dewi, Zulia Almaida Siregar
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引用次数: 1

Abstract

In carrying out promotions, it is also necessary to pay for the manufacture of brochures, banners and other promotional media to provide information to prospective students and attract prospective students to register. Determining the location of the promotion is one of the success factors in promotional activities. In this study, the Artificial Neural Network will be used to predict the location of the promotion. Backpropagation is one of the best artificial neural network methods used for prediction, this method is widely used by researchers in predicting a problem. The data analysis tool used is Matlab or what we call the (Matrix Laboratory) which is a program to analyze and compute numerical data, and Matlab is also an advanced mathematical programming language, which was formed on the premise of using the properties and forms of matrices. From the results of the algorithm used, it is expected to get good accuracy results with some architectural experiments later. So that this research can be an indicator to optimize promotions in the following year in order to attract prospective students to register for AMIK and STIKOM Tunas Bangsa Pematangsiantar
反向传播模型在未来新生学校选址预测中的推广优化
在进行促销活动时,还需要付费制作宣传册、横幅等宣传媒体,向准学生提供信息,吸引准学生报名。确定促销地点是促销活动成功的因素之一。在本研究中,将使用人工神经网络来预测促销的位置。反向传播是人工神经网络预测中最好的方法之一,被研究人员广泛应用于预测问题。所使用的数据分析工具是Matlab或我们所说的(Matrix Laboratory),它是一种分析和计算数值数据的程序,Matlab也是一种先进的数学编程语言,它是在利用矩阵的性质和形式的前提下形成的。从所使用的算法的结果来看,期望在以后的一些建筑实验中得到较好的精度结果。因此,这项研究可以作为一个指标,以优化促销在接下来的一年,以吸引未来的学生注册AMIK和STIKOM Tunas Bangsa Pematangsiantar
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