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Application of data mining for Indonesian products export in South Korea using clustering: Indonesia Trade Promotion Center Busan

机译:数据挖掘对印尼产品的应用在韩国使用聚类:印度尼西亚贸易促销中心釜山

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This research purpose is to classify data export products of Indonesia against South Korea. The clustering method used in this research was the K-Means method, in K-Means cluster had a good degree of accuracy. This research examines how the use of the K-means method in case studies export products Indonesia against South Korea. From the results of clustering using K-Means method based on the value of the USD and Kg, then the generated 3 (three) clusters with cluster values are high, medium and low. Based on those results suggest that K-Means method can be used for inventory control of product reference or as Indonesia Indonesia Trade Promotion Center (ITPC) in Busan to view any export products should be retained and what are the export products should be improved to be promoted in South Korea so as to increase the number of export products of Indonesia against South Korea.
机译:这项研究目的是将印度尼西亚的数据出口产品进行分类,反对韩国。 本研究中使用的聚类方法是K-Means方法,在K均值群中具有良好程度的准确性。 本研究探讨了如何使用K-Means方法,以防案例研究印度尼西亚反对韩国。 根据基于USD和kg的值的k-means方法,群体的结果从k-means方法,那么具有簇值的生成的3(三个)群集是高,中低的。 基于这些结果表明,K-means方法可用于产品参考资料或印度尼西亚印度尼西亚贸易促销中心(ITPC)在釜山中查看任何出口产品应保留,应提高出口产品是什么 在韩国晋升,以增加印度尼西亚的出口产品对阵韩国。

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