Skripsi

PENERAPAN ALGORITMA K-MEANS UNTUK CLUSTERING DATA PENDUDUK MISKIN PER KABUPATEN/KOTA DI PULAU SUMATERA

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Penilaian

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overty is a problem that exists in every region in Indonesia. There are many factors that cause poverty that influence the level of welfare of the population. Therefore, it is necessary to group data n the poor population of districts/cities to assist in policy decision making. This research uses the K-Means algorithm which is a technique in data mining. Grouping large amounts of data with relatively fast and efficient computing time is the advantage of the K-Means algorithm. This research aims to detemine the results of grouping poverty levels from low to highest levels. The results of the grouping will be evaluated using the Davies-Boulding Index (DBI) value. After testing and evaluating 3 times with 10 groups, it was found that the 10th group was the best result. The comparison of results in 2020 obtained for the district/city category, the lowest was 4 group members and the highest 28 group members. In 2021, the lowest was 4 group members and the highest was 30 group members for the district/city category. In 2022, the lowest was 4 group members for the district/city category and the highest was 29 group members.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2407001699	T141362	T1413622024	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1413622024

Publisher

Inderalaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2024

Collation

xvii, 85 hlm.; Ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

005.707

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Prodi Teknik Informatika
Data dalam sistem-sistem komputer

Specific Detail Info

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Statement of Responsibility

SEPTA

Other version/related

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