{"title":"Penerapan Jaringan Saraf Tiruan Learning Vector Quantization Untuk Pemetaan Wilayah Berpenduduk Miskin di Provinsi Maluku","authors":"D. L. Rahakbauw, V. Ilwaru","doi":"10.30598/tensorvol1iss1pp25-30","DOIUrl":null,"url":null,"abstract":"Badan Pusat Statistik (BPS) stated that the number of poor people in Indonesia reached 28.01 million people based on data as of March 2016. This figure is around 10.86 percent of the national population. Province of Maluku as the third poor contributor of all provinces in Indonesia reached 27.74 percent. Note that, there are 8 of total 11 districts/cities in Maluku which are determined as underdeveloped regions (Kementerian PDT, 2015), Maluku Barat Daya (MBD) is one of them. Based on data from BPS, in 2014 the percentage of poor people in district of MBD reached 28.33 percent being the second highest district in Maluku after Maluku Tenggara Barat (MTB). It is quite difficult make the poverty level of MBD lower, due to a large number of villages in MBD have some economic access isolations because of geographical conditions. Various programs and policies in social and health have been done to solve this poverty problem, but still could not overcome this problem yet. \nIn this paper we have grouped the districts/cities of Maluku based on poverty factors using Learning Vector Quantization (LVQ) method. The results of this research showed that there are 5 poverty clusters in Maluku. Those are: Cluster 1 consists of Maluku Tenggara Barat, Maluku Utara dan Buru; cluster 2 consists of Maluku Tengah; cluster 3 consists of Kep. Aru, Seram Bagian Barat dan Seram Bagian Timur, cluster 4 consists of Maluku Barat Daya dan Buru Selatan; and cluster 5 consists of Ambon and Tual. Each cluster describes the poverty level with respect to its Partition matrix respectively. The results that we obtained also show that cluster 4 has the highest poverty level.","PeriodicalId":294430,"journal":{"name":"Tensor: Pure and Applied Mathematics Journal","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tensor: Pure and Applied Mathematics Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30598/tensorvol1iss1pp25-30","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
印尼统计局(BPS)表示,根据2016年3月的数据,印尼贫困人口数量达到2801万人。这一数字约占全国人口的10.86%。马鲁古省是印度尼西亚所有省份中第三贫穷的省份,占27.74%。值得注意的是,马鲁库11个区/市中有8个被确定为不发达地区(Kementerian PDT, 2015),马鲁库巴拉特达亚(MBD)是其中之一。根据BPS的数据,2014年MBD地区的贫困人口比例达到28.33%,是马鲁古第二高的地区,仅次于马鲁古登加拉巴拉特(MTB)。由于地理条件的限制,MBD大量村庄存在一定程度的经济准入隔离,降低MBD贫困水平难度较大。社会和卫生方面的各种方案和政策已经解决了这一贫困问题,但仍然无法克服这一问题。本文采用学习向量量化(LVQ)方法,对马鲁古省各区/市进行了贫困因素分组。研究结果表明,马鲁古有5个贫困集群。它们是:集群1由Maluku Tenggara Barat, Maluku Utara dan Buru组成;集群2包括马鲁古登加;集群3由Kep组成。Aru, Seram Bagian Barat dan Seram Bagian Timur,集群4由Maluku Barat Daya dan Buru Selatan组成;星团5由Ambon和Tual组成。每个聚类分别描述相对于其划分矩阵的贫困水平。我们得到的结果还表明,第四集群的贫困程度最高。
Penerapan Jaringan Saraf Tiruan Learning Vector Quantization Untuk Pemetaan Wilayah Berpenduduk Miskin di Provinsi Maluku
Badan Pusat Statistik (BPS) stated that the number of poor people in Indonesia reached 28.01 million people based on data as of March 2016. This figure is around 10.86 percent of the national population. Province of Maluku as the third poor contributor of all provinces in Indonesia reached 27.74 percent. Note that, there are 8 of total 11 districts/cities in Maluku which are determined as underdeveloped regions (Kementerian PDT, 2015), Maluku Barat Daya (MBD) is one of them. Based on data from BPS, in 2014 the percentage of poor people in district of MBD reached 28.33 percent being the second highest district in Maluku after Maluku Tenggara Barat (MTB). It is quite difficult make the poverty level of MBD lower, due to a large number of villages in MBD have some economic access isolations because of geographical conditions. Various programs and policies in social and health have been done to solve this poverty problem, but still could not overcome this problem yet.
In this paper we have grouped the districts/cities of Maluku based on poverty factors using Learning Vector Quantization (LVQ) method. The results of this research showed that there are 5 poverty clusters in Maluku. Those are: Cluster 1 consists of Maluku Tenggara Barat, Maluku Utara dan Buru; cluster 2 consists of Maluku Tengah; cluster 3 consists of Kep. Aru, Seram Bagian Barat dan Seram Bagian Timur, cluster 4 consists of Maluku Barat Daya dan Buru Selatan; and cluster 5 consists of Ambon and Tual. Each cluster describes the poverty level with respect to its Partition matrix respectively. The results that we obtained also show that cluster 4 has the highest poverty level.