Agglomerative Hierarchical Clustering Dengan Berbagai Pengukuran Jarak Dalam Mengklaster Daerah Berdasarkan Tingkat Kemiskinan.

Sukemi, Sukemi (2019) Agglomerative Hierarchical Clustering Dengan Berbagai Pengukuran Jarak Dalam Mengklaster Daerah Berdasarkan Tingkat Kemiskinan. Annual Research Seminar Computer Science and ICT (ARS), 5 (1). pp. 145-147. ISSN 979-587-573-6

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Abstract

Information that is efficient, effective, right on target and can be trusted, is a powerful instrument to be the basis for policy making. This has become an important aspect in supporting problem-solving strategies, one of which is poverty. Problems that become global and national issues. The purpose of this research is to develop a framework that applies the CRISP- DM methodology and the Agglomerative Hierarchical Clustering technique using several variations of distance measurements, in producing regional cluster analysis based on poverty levels in the East Kalimantan region.

Item Type: Article
Subjects: Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions: 09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User: Dr. Sukemi Sukemi
Date Deposited: 18 Jan 2022 07:28
Last Modified: 18 Jan 2022 07:28
URI: http://repository.unsri.ac.id/id/eprint/61313

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