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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