Mapping Assistance For The Distribution Of Nine Food Staples To People Groups In Joglo Village Using K-Means Method

I. Prabowo, Bela Septiana
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Abstract

There are so many people live in Joglo village. However, sometimes  the government  feel confuse to decide the distribution of staple necessities.  The decision sometimes feel unfair dan get disappointing result because it is not appropriate to the real condition in certain family. The purpose of this study is to create model of mapping system for staple food assistance in Joglo village using the K-Means method. The method of this research use collecting data, modeling data using K-Means, Application Creation, Application Testing. There are some steps on collecting data, such as: observation, interview and literature case. The data came from the result of population census survey on 2020. Its used K-Means Method in data modelig stage. The data has been analyzed and modeled using the application of the K-Mean Method and  the stage of making an application using PHP in accordance with the stage pattern in the K-Mean method, then application testing is carried out whether it is appropriate for the K-Means method modeller. Mapping system for staple food assistance in Joglo Village using the K-means method that has been made has alternative input data and criteria. The result of this study has reciever mapping food in Joglo Village forming 3 clusters. There are 21 people on the first cluster, 16 people on the second cluster, 13 people on the third cluster.
使用K-Means方法为Joglo村的人群分配九种主食提供地图援助
有很多人住在Joglo村。然而,有时政府在决定基本生活必需品的分配时感到困惑。决定有时感觉不公平,但得到令人失望的结果,因为它不适合某些家庭的实际情况。本研究的目的是利用K-Means方法建立Joglo村主粮援助测绘系统模型。本研究采用数据收集、K-Means建模、应用创建、应用测试等方法。收集数据的步骤有:观察、访谈和文献案例。数据来自2020年人口普查结果。在数据建模阶段采用K-Means方法。利用K-Mean方法的应用对数据进行分析和建模,并根据K-Mean方法中的阶段模式使用PHP进行应用阶段,然后对K-Means方法建模器是否适合进行应用测试。使用K-means方法的Joglo村主食援助测绘系统具有可选择的输入数据和标准。本研究的结果是在Joglo村形成了3个群体。第一个集群有21个人,第二个集群有16个人,第三个集群有13个人。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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