Ingka Rizkyani Akolo, A. R. Pratama, Asriyati Nadjamuddin
{"title":"基于村庄潜力指标的模糊 C-Means 法和 Ward 法对村庄聚类的比较","authors":"Ingka Rizkyani Akolo, A. R. Pratama, Asriyati Nadjamuddin","doi":"10.37905/euler.v11i2.21820","DOIUrl":null,"url":null,"abstract":"Bone Bolango is one of the districts that has experienced many village and sub-district expansion processes. This expansion process changes the village's potential data. Village potential is the carrying capacity for developing villages in order to improve community welfare. In order to accelerate village development, it is necessary to group villages according to their characteristics so that development is more focused and on target. The aim of this research is to group villages based on indicators of village potential so that groups of villages that have the same characteristics can be obtained, as well as to find out the best method for grouping villages in Bone Bolango Regency. The research results show that the optimum cluster for grouping villages in Bone Bolango Regency based on village potential indicators is the cluster using the ward method because it provides the smallest Xie-Beni index value compared to the fuzzy c-means method. The optimum number of clusters is three clusters. Cluster 1 has high average characteristics consisting of 57 villages, cluster 2 has low average characteristics (except livestock production) consisting of 94 villages and cluster 3 has characteristics of large area and high food production consisting of 9 villages.","PeriodicalId":504964,"journal":{"name":"Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi","volume":"64 11","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Perbandingan Metode Fuzzy C-Means dan Ward Pada Pengelompokkan Desa Berdasarkan Indikator Potensi Desa\",\"authors\":\"Ingka Rizkyani Akolo, A. R. Pratama, Asriyati Nadjamuddin\",\"doi\":\"10.37905/euler.v11i2.21820\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Bone Bolango is one of the districts that has experienced many village and sub-district expansion processes. This expansion process changes the village's potential data. Village potential is the carrying capacity for developing villages in order to improve community welfare. In order to accelerate village development, it is necessary to group villages according to their characteristics so that development is more focused and on target. The aim of this research is to group villages based on indicators of village potential so that groups of villages that have the same characteristics can be obtained, as well as to find out the best method for grouping villages in Bone Bolango Regency. The research results show that the optimum cluster for grouping villages in Bone Bolango Regency based on village potential indicators is the cluster using the ward method because it provides the smallest Xie-Beni index value compared to the fuzzy c-means method. The optimum number of clusters is three clusters. Cluster 1 has high average characteristics consisting of 57 villages, cluster 2 has low average characteristics (except livestock production) consisting of 94 villages and cluster 3 has characteristics of large area and high food production consisting of 9 villages.\",\"PeriodicalId\":504964,\"journal\":{\"name\":\"Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi\",\"volume\":\"64 11\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.37905/euler.v11i2.21820\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37905/euler.v11i2.21820","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
Bone Bolango 是经历过多次村庄和分区扩展过程的地区之一。这种扩张过程改变了村庄的潜在数据。村庄潜力是为改善社区福利而发展村庄的承载能力。为了加快村庄发展,有必要根据村庄的特点对村庄进行分组,以便使发展更有针对性和目标性。本研究的目的是根据村庄潜力指标对村庄进行分组,以获得具有相同特征的村庄组,并找出对 Bone Bolango 地区村庄进行分组的最佳方法。研究结果表明,根据村庄潜力指标对 Bone Bolango 摄政区村庄进行分组的最佳聚类是采用选区法的聚类,因为与模糊 c-means 法相比,选区法提供的 Xie-Beni 指数值最小。最佳聚类数为三个聚类。第 1 聚类具有较高的平均特征,由 57 个村庄组成;第 2 聚类具有较低的平均特征(畜牧生产除外),由 94 个村庄组成;第 3 聚类具有面积大和粮食产量高的特征,由 9 个村庄组成。
Perbandingan Metode Fuzzy C-Means dan Ward Pada Pengelompokkan Desa Berdasarkan Indikator Potensi Desa
Bone Bolango is one of the districts that has experienced many village and sub-district expansion processes. This expansion process changes the village's potential data. Village potential is the carrying capacity for developing villages in order to improve community welfare. In order to accelerate village development, it is necessary to group villages according to their characteristics so that development is more focused and on target. The aim of this research is to group villages based on indicators of village potential so that groups of villages that have the same characteristics can be obtained, as well as to find out the best method for grouping villages in Bone Bolango Regency. The research results show that the optimum cluster for grouping villages in Bone Bolango Regency based on village potential indicators is the cluster using the ward method because it provides the smallest Xie-Beni index value compared to the fuzzy c-means method. The optimum number of clusters is three clusters. Cluster 1 has high average characteristics consisting of 57 villages, cluster 2 has low average characteristics (except livestock production) consisting of 94 villages and cluster 3 has characteristics of large area and high food production consisting of 9 villages.