The Sriwijaya University Library

  • Home
  • Information
  • News
  • Help
  • Librarian
  • Login
  • Member Area
  • Select Language :
    Arabic Bengali Brazilian Portuguese English Espanol German Indonesian Japanese Malay Persian Russian Thai Turkish Urdu

Search by :

ALL Author Subject ISBN/ISSN Advanced Search

Last search:

{{tmpObj[k].text}}
Image of PENERAPAN DATA MINING UNTUK CLUSTERING DATA PENDUDUK MISKIN DI KABUPATEN REJANG LEBONG MENGGUNAKAN METODE K-MEANS

Skripsi

PENERAPAN DATA MINING UNTUK CLUSTERING DATA PENDUDUK MISKIN DI KABUPATEN REJANG LEBONG MENGGUNAKAN METODE K-MEANS

Syafrinka, Almayda Merin - Personal Name;

Penilaian

0,0

dari 5
Penilaian anda saat ini :  

The Social Service is a regional apparatus in charge of the social life of the community, including by registering the impoverished or underprivileged. Also the poverty line in Rejang Lebong Regency, Curup-Bengkulu increased in 2020 due to the pandemic. Grouping the poor or impoverished based on existing attributes by analyzing data based on clustering techniques is very necessary. In other words, this method serves to group data based on unique similarities and explain output patterns per cluster and can optimize poverty countermeasures in Rejang Lebong districts. Therefore, it's necessary to implement data mining at the Rejang Lebong’s Social Service, especially in the field of Social Empowerment and Handling of the impoverished in order to process poverty data into more informative data. This research uses K-Means Clustering Methods. Dinas Sosial merupakan instansi perangkat daerah yang bertugas di bidang sosial kehidupan masyarakat, termasuk dengan mendata masyarakat kurang mampu atau miskin. Dan garis kemiskinan di Kabupaten Rejang Lebong,Curup-Bengkulu meningkat lagi di tahun 2020 karena terdampak pandemi. Pengelompokkan masyarakat miskin berdasarkan atribut telah ada dengan menganalisis data berdasarkan teknik klasterisasi sangat dibutuhkan. Dengan kata lain metode ini berfungsi untuk mengelompokkan data berdasarkan kemiripan unik dan menjelaskan pola keluaran per klaster dan dapat mengoptimalkan penanggulangan kemiskinan di Kabupaten Rejang Lebong. Maka dari itu dibutuhkan implementasi data mining pada Dinas Sosial Rejang Lebong khususnya Bidang Pemberdayaan Sosial & Penanganan Fakir Miskin agar dapat memproses data kemiskinan menjadi sebuah data yang lebih informatif. Penelitian ini mengggunakan metode K-Means Clustering.


Availability
Inventory Code Barcode Call Number Location Status
2107002614T50436T504362021Central Library (Referens)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T504362021
Publisher
Inderalaya : Prodi Sistem Informasi, Fakultas Ilmu Komputer Universitas Sriwijaya., 2021
Collation
xvi, 78 hlm,: ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
005.360 7
Content Type
Text
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Prodi Sistem Informasi
Program untuk Komputer Personal, Sistem Informasi
Specific Detail Info
-
Statement of Responsibility
MURZ
Other version/related

No other version available

File Attachment
  • PENERAPAN DATA MINING UNTUK CLUSTERING DATA PENDUDUK MISKIN DI KABUPATEN REJANG LEBONG MENGGUNAKAN METODE K-MEANS
Comments

You must be logged in to post a comment

The Sriwijaya University Library
  • Information
  • Services
  • Librarian
  • Member Area

About Us

As a complete Library Management System, SLiMS (Senayan Library Management System) has many features that will help libraries and librarians to do their job easily and quickly. Follow this link to show some features provided by SLiMS.

Search

start it by typing one or more keywords for title, author or subject

Keep SLiMS Alive Want to Contribute?

© 2025 — Senayan Developer Community

Powered by SLiMS
Select the topic you are interested in
  • Computer Science, Information & General Works
  • Philosophy & Psychology
  • Religion
  • Social Sciences
  • Language
  • Pure Science
  • Applied Sciences
  • Art & Recreation
  • Literature
  • History & Geography
Icons made by Freepik from www.flaticon.com
Advanced Search