Ilham Adnan Kasoqi, Memi Nor Hayati, Rito Goejantoro
{"title":"PENGELOMPOKAN DESA ATAU KELURAHAN DI KUTAI KARTANEGARA MENGGUNAKAN ALGORITMA DIVISIVE ANALYSIS","authors":"Ilham Adnan Kasoqi, Memi Nor Hayati, Rito Goejantoro","doi":"10.26714/jsunimus.9.2.2021.101-108","DOIUrl":null,"url":null,"abstract":"Potential Villages (PODES) provide data on the existence, availability and development of the potential of each government administrative area. In order to make it easier for governments to make policies for a region, it is necessary to group the village and sub-districts. Cluster analysis is an analysis that aims to group objects based on the information that found in the data. One of the cluster analysis methods is the divisive analysis, which is a hierarchical grouping method with a top-down approach, where all objects are placed in one cluster and then sequentially divided into separate groups. This research aim to group villages or sub-districts in Kutai Kartanegara based on the determinants of village backwardness and obtaining the silhouette coefficient value from the optimal cluster analysis using the divisive analysis algorithm. The data used is the 2018 PODES data in Kutai Kartanegara and used 15 variables from natural and environmental factors, facilities infrastructure and access factors as well as socio-economic factors of the population. The results of the optimal cluster formed in the grouping of villages or sub-districts in Kutai Kartanegara using the divisive analysis method are 2 clusters. Cluster 1 consisting of 230 villages or sub-districts and cluster 2 consisting of 2 sub-districts. Silhouette coefficient value for data validation from clustering village or sub-districts in Kutai Kartanegara using the divisive analysis method produces 2 clusters is 0,744 which states that the cluster structure formed in this grouping is a strong structure.","PeriodicalId":183562,"journal":{"name":"Jurnal Statistika Universitas Muhammadiyah Semarang","volume":"303 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Statistika Universitas Muhammadiyah Semarang","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26714/jsunimus.9.2.2021.101-108","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

潜力村(PODES)提供关于每个政府行政区域的存在、可用性和潜力发展的数据。为了使政府更容易为一个地区制定政策,有必要将村和街道分组。聚类分析是一种旨在根据数据中发现的信息对对象进行分组的分析。其中一种聚类分析方法是分裂分析,这是一种自上而下的分层分组方法,将所有对象放在一个聚类中,然后依次分成单独的组。本研究的目的是基于村庄落后的决定因素,对库泰Kartanegara村或街道进行分组,并利用分裂分析算法从最优聚类分析中获得剪影系数值。使用的数据是Kutai Kartanegara的2018年PODES数据,并使用了15个变量,包括自然和环境因素、设施基础设施和准入因素以及人口的社会经济因素。用分裂分析法对库台Kartanegara村或街道进行分组后,形成的最优聚类结果为2个聚类。第一组由230个村庄或街道组成,第二组由2个街道组成。利用分裂分析法对库台Kartanegara村或街道的聚类数据进行验证,得到2个聚类的剪影系数值为0.744,说明该聚类所形成的聚类结构为强结构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PENGELOMPOKAN DESA ATAU KELURAHAN DI KUTAI KARTANEGARA MENGGUNAKAN ALGORITMA DIVISIVE ANALYSIS
Potential Villages (PODES) provide data on the existence, availability and development of the potential of each government administrative area. In order to make it easier for governments to make policies for a region, it is necessary to group the village and sub-districts. Cluster analysis is an analysis that aims to group objects based on the information that found in the data. One of the cluster analysis methods is the divisive analysis, which is a hierarchical grouping method with a top-down approach, where all objects are placed in one cluster and then sequentially divided into separate groups. This research aim to group villages or sub-districts in Kutai Kartanegara based on the determinants of village backwardness and obtaining the silhouette coefficient value from the optimal cluster analysis using the divisive analysis algorithm. The data used is the 2018 PODES data in Kutai Kartanegara and used 15 variables from natural and environmental factors, facilities infrastructure and access factors as well as socio-economic factors of the population. The results of the optimal cluster formed in the grouping of villages or sub-districts in Kutai Kartanegara using the divisive analysis method are 2 clusters. Cluster 1 consisting of 230 villages or sub-districts and cluster 2 consisting of 2 sub-districts. Silhouette coefficient value for data validation from clustering village or sub-districts in Kutai Kartanegara using the divisive analysis method produces 2 clusters is 0,744 which states that the cluster structure formed in this grouping is a strong structure.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信