基于先验算法的工程材料采购预测方法的实现。Padat Karya Konstruksi

Nadia Elisa Suhardi, Maryaningsih Maryaningsih, Rizka Tri Alinse
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引用次数: 0

摘要

在预测商品的购买情况时,可以使用的方法有很多,其中,根据公司根据所购商品之间的关系进行的购买过程,使用数据挖掘方法和Priori算法对购买数据进行处理。通过使用先验算法,本例中的公司是CV。Padat Karya Konstruksi可以估算出工人所需的建筑材料数量,这是由于CV购买了大量货物。Padat Karya Konstruksi的作品。先验算法采用表格形式进行数据转换,确定最小支持度和最小置信度,形成1项集候选组合模式,然后计算每个项集中出现的次数。因此从17(17)个数据中得出,经常购买的项目是水泥多达11(11)次,劈裂石8(8)次,混凝土砂多达8(8)次,支撑值为25%,置信度为75%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Implementation Of Apriori Algorithm Methods For Predicting Project Material Purchases At CV. Padat Karya Konstruksi
In predicting the purchase of goods, there are many methods that can be used, among others, by processing purchase data using Data Mining method accompanied by Priori Algorithm based on the purchasing process carried out by the company based on the relationship between the goods purchased. By using the a priori algorithm, the company in this case is CV. Padat Karya Konstruksi can estimate the number of building materials needed by workers this is due to the large number of goods purchases at CV. Padat Karya Konstruksi to match the work. The stages of the a priori algorithm used are data transformation in tabular table form, determining the minimum value of support and minimum confidence, formation of 1-item set candidate combination pattern then counting the number of occurrences in each item set. So that it is obtained from 17 (seventeen) data, items that are often purchased are cement as much as 11 (eleven) times, split stone 8 (eight) times, and concrete sand as much as 8 (eight) times with a support value of 25% and a confidence value of 75%.
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