Please use this identifier to cite or link to this item: http://repository.unmul.ac.id/handle/123456789/22791
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dc.contributor.authorWahyuni, Nanda Anggun-
dc.contributor.authorHayati, Memi Nor-
dc.contributor.authorRizki, Nanda Arista-
dc.date.accessioned2022-03-10T13:36:57Z-
dc.date.available2022-03-10T13:36:57Z-
dc.date.issued2021-06-21-
dc.identifier.issn2798-3455-
dc.identifier.urihttp://repository.unmul.ac.id/handle/123456789/22791-
dc.description.abstractThe underdeveloped areas are generally the districts which are relatively underdeveloped compared to other regions on a national scale. Determination of underdeveloped villages is often done in order to determine the distribution of government assistance so that assistance can be distributed appropriately. The identification is based on facilities, infrastructure, access, social, population and economy provided in the Village Potential data (PODES). The concept of grouping based on regional or spatial is done to find out certain characteristics in an area. HDBSCAN is a grouping concept with a parameter called Mpts. The purpose of this study is to know the number of clusters formed in the grouping of underdeveloped villages / urban areas in Kutai Kartanegara Regency using the HDBSCAN method. The Mpts parameters that is used in this study is from 2 to 6. Based on the results of the analysis, the clusters formed in the grouping of underdeveloped villages / urban areas in Kutai Kartanegara Regency using the HDBSCAN method, were 3 clusters. Cluster 0 consists of 19 villages / urban areas , cluster 1 consists of 4 villages / urban areas and cluster 2 consists of 61 villages / urban areas. Based on the analysis, villages / urban areas included in cluster 1 could be the main target of the government in providing assistance and development of regional facilities / infrastructure.en_US
dc.publisherJurusan Matematika, Fakultas Matematika dan Ilmu Pengetahuan Alamen_US
dc.subjectSpatialen_US
dc.subjectHDBSCANen_US
dc.subjectVillage Potentialen_US
dc.titleMetode Hierarchical Density-Based Spatial Clustering of Application with Noise (HDBSCAN) Pada Wilayah Desa/Kelurahan Tertinggal di Kabupaten Kutai Kartanegaraen_US
dc.typeArticleen_US
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