Penerapan Metode K-Means Dalam Mengelompokkan Persebaran Lahan Kritis Di Indonesia Berdasarkan Provinsi
DOI:
https://doi.org/10.30865/resolusi.v2i4.335Abstract
The study aims to group the distribution of critical land in Indonesia by province. To solve this problem, researchers applied the K-Means Algorithm method. Where the source of research data is collected based on documents - documents of Information on The Extent and Dissemination of Critical Land By Province produced by the Central Statistics Agency (BPS). The data used in the study was data from 2011, 2013 and 2018 consisting of 34 provinces. Data will be processed by clustering in 2 clusters, namely clusters of high critical land distribution rates and clusters of low critical land distribution rates. The high cluster amounted to 4 data, namely the provinces of North Sumatra, Jambi, East Java, and Central Kalimantan. With the conduct of research can contribute in improving the performance of Balai Pengelolaan Daerah Aliran Sungai dan Hutan Lindung (BPDASHL) on the process of fixing and tackling critical land in the provinces in Indonesia.
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