应用k -均值聚类技术监测阿加威县稻田肥料利用水平

I. Prabowo, Hendro Wijayanto, Sujud Aji Wantoro
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引用次数: 1

摘要

肥料是一种给予植物的物质,可以作为植物的食物。肥料本身分为两种,即无机肥料和有机肥料。化肥对农民的需求是非常重要的,尤其是农民。因此,肥料需要量应能在监测中不致出现不足。本研究的目的是使用k-均值算法对Ngawi地区每个城镇的肥料使用情况进行分组。要解决的问题是如何运用k-means算法对恩加威每个城镇的肥料需求进行分类。K-means是一种聚类算法,可以根据数据相似度将一个对象归为一组。聚类结果K-means聚类在第一组高(聚类1)包含6个,在第二组中(聚类2)包含2个小区,而在第三组低(聚类3)包含11个小区。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of K-Means Clustering to Monitoring the level of Fertilizer Usage in Rice Fields in Ngawi Regency
Fertilizer is a substance given to plants that could be food for plants. Fertilizer  itself divided into two types, that  is  inorganic  fertilizers  and  organic  fertilizer.  Fertilizer  is  very important  to  the  needs  of farmers,  especially  farmers.  Therefore  fertilizer  needs should be able  to in monitoring  in  order  not to occur lack. The purpose of this study is a grouping of the use of fertilizer in every town in the districts of Ngawi with k-Means algorithm. The formulation of the problem to overcome is how to apply the method of k-means  algorithm  to  categorize  fertilizer  needs  in  every  town  in  the  Ngawi.  K-means  is  clustering algorithm where one object can be in group based on data similarities. Clustering results K-means Clustering is seen in the first group high (Cluster 1) contains 6, In the second group medium (Cluster 2) contains 2 sub-districts, while in the third group low (cluster 3rd) contains 11 sub-districts.
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