ICONNET产品销售预测天真的贝斯算法的应用

Chindy Clara Edina Aprila, Febrian Wahyu Christanto
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引用次数: 0

摘要

ICONNET是PT Indonesia Comnets Plus面向零售客户的产品,是一家新的互联网提供商。ICONNET打算为印尼人民提供最好的服务。他们需要有一个策略来继续增加产品的销售。在销售过程中,增加产品销售的一种方法是了解产品向客户销售的历史。是否符合销售目标?因此,如果没有达到销售目标,它可以作为一个绩效评估,特别是对市场和销售团队。因此,作者通过实现朴素贝叶斯分类器算法创建了一个销售预测系统,该系统可用于根据先前记录的数据预测ICONNET产品的销售。采用黑盒法和性能测试对系统进行测试。结果输出是一个基于web的系统。检测结果正确率为89.189%。而性能测试结果获得a级分数(91%)。希望在以后的开发中能够更加注重用户的需求。
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PENERAPAN ALGORITMA NAÏVE BAYES UNTUK PREDIKSI PENJUALAN PRODUK ICONNET
ICONNET, which is a product from PT Indonesia Comnets Plus for the retail customer segment, is a new internet provider. ICONNET intends to provide the best for the Indonesian people. They need to have a strategy in order to continue to increase sales of their products. In the sales process, one way to increase product sales is to know the history of product sales to customers. Is it in accordance with the sales target or not. So if the sales target has not been met, it can be used as a performance evaluation, especially for the marketing and sales team. Therefore, the authors created a sales prediction system by implementing the Naive Bayes Classifier Algorithm which can be used to predict sales of ICONNET products based on previously recorded data. Testing the system with the black box method and performance testing. The resulting output is a web-based system. The percentage of accuracy test results are 89.189%. While the results of performance testing obtained a score with grade A (91%). It is hoped thet in the future this system can be developed with more attention to user needs.
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