k -均值聚类方法在橡胶价格分组中的应用——以蚌古鲁省胜匡加亚村为例

K. Khairullah, M. H. Rifqo, Harry Witriyono, Adelia Karolina
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引用次数: 0

摘要

Sengkuang Jaya村是位于明古鲁省的一个地区。在村里,橡胶的价格仍然是手工计算的。本研究拟应用k-means聚类方法,根据Bengkulu省Sengkuang Jaya村农民拥有的橡胶质量计算橡胶价格。本研究的目的是根据Bengkulu省Sengkuang Jaya村的橡胶质量来确定价格。本研究的数据收集方法采用访谈法和观察法。结果表明,15份胶乳样本数据中,2周及以上的橡胶价格最高,2周以下的橡胶价格最高,包括聚类2。测试结果表明,rapidminer工具运行良好,没有出现任何错误。根据研究结果,可以建议使用相同类型的数据,但可以使用更好的方法进行进一步的研究,例如使用模糊C-Means算法,硬C-Means算法以及完成可能长达1年的橡胶储存样本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Application of K-Means Clustering Method for Rubber Price Grouping in Sengkuang Jaya Village Bengkulu Province
Sengkuang Jaya village is an area located in Bengkulu province. The calculation of price for rubber is still calculated manually in the village. This study wants to apply the k-means clustering method for calculating rubber prices according to the quality of rubber owned by farmers in Sengkuang Jaya Village, Bengkulu Province. This study aimed to determine prices based on rubber quality in Sengkuang Jaya Village,Bengkulu Province. The tehnique of collecting the data of this study used interview and observation.The results showed that from 15 samples of rubber latex data taken,the price of rubber with the highest cluster was found for rubber 2 weeks and over and for rubber 2 weeks down including cluster 2.The results of testing the rapidminer tools run well without any errors. Base on the result of the study can be suggested that further research can be developed with the same type of data but using better methods such as using the Fuzzy C-Means algorithm, Hard C-Means and completing the sample which may be up to 1 year of rubber storage.
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