Skripsi

METODE K-MEANS UNTUK PENGELOMPOKAN KABUPATEN/KOTA DI PROVINSI JAMBI BERDASARKAN INDIKATOR PENDIDIKAN DENGAN TIGA TINGKATAN

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Penilaian

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Cluster analysis is a multivariate statistical analysis method used to group variables or objects into several groups that have certain similar characteristics so that each group will contain homogeneous objects. K-Means is one of the non-hierarchical data clustering or partitional clustering methods. Education is a fundamental need that must be fulfilled in social life. The problem of uneven education in each district / city in Jambi Province. To see the level of education in districts / cities in Jambi Province based on educational indicators, so that clustering of districts / cities in Jambi Province based on educational indicators at three levels, namely primary, secondary and tertiary. The goal is to find out the best cluster at each level of education. The method used is K-Means. Data on education indicators analyzed include Gross Enrollment Rate (APK), School Participation Rate (APS), Pure Enrollment Rate (APM), Literacy Rate (AMH), and Average Years of Study (RLB) sourced from BPS Jambi Province publications. The results showed that the best cluster results of districts / cities in Jambi Province based on education indicators with three levels in 2022 by applying K-means Cluster. At the primary level of education, the best clusters are obtained in 4 clusters with a weak structure that tends not to occur clustering. At the secondary level of education, the best clusters were obtained in 3 clusters. In higher education, the best clusters are obtained in 2 clusters, namely cluster 1 Jambi City and Full River City, the rest are in cluster 2.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2407005125	T151714	T1517142024	Central Library (References)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1517142024

Publisher

Indralaya : Prodi Ilmu Matematika, Fakultas Matematika Dan Ilmu Pengetahuan Alam Universitas Sriwijaya., 2024

Collation

xiv, 61 hlm.; ilus.; tab, 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

510.285 07

Content Type

Text

Media Type

unmediated

Carrier Type

other (computer)

Edition

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Subject(s)

Pengolahan dan Analisa Data di Bidang Matematika
Prodi Ilmu Matematika

Specific Detail Info

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Statement of Responsibility

SEW

Other version/related

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