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IMPLEMENTASI METODE K-MEANS CLUSTERING UNTUK PENENTUAN TINGKAT URGENSI PELAKSANAAN PROGRAM PNPM MANDIRI

YUSUF, NUKRAH (2011) IMPLEMENTASI METODE K-MEANS CLUSTERING UNTUK PENENTUAN TINGKAT URGENSI PELAKSANAAN PROGRAM PNPM MANDIRI. Other thesis, University of Muhammadiyah Malang.

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Abstract

PNPM Mandiri is a national program of poverty alleviation, mainly in community empowerment based program. The massive number of data in work program needs solutions to manage, so that it can give and serve good information. Simply, we can define data mining as the extraction of information or essential pattern from the data in a large database - so it can be a valuable information. Clustering in data mining is necessary to find distribution pattern in a database. It is useful for data analyzing process. The principal of clustering is to maximize similarity among a class? members, and to minimize interclass similarity. K-Means is a method of non-hierarchy data clustering, which tries to partition the existing data into one or more forms of clusters/groups. Within K-Means Clustering algorithm, the massive work program can be united and grouped into three clusters, which are urgent; medium; and non-urgent work programs.

Item Type: Thesis (Other)
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering > Department of Informatics (55201)
Depositing User: Halimatus Zahroh
Date Deposited: 17 Feb 2015 14:31
Last Modified: 17 Feb 2015 14:31
URI : http://eprints.umm.ac.id/id/eprint/16335

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