Skripsi

ANALISIS PERBANDINGAN ALGORITMA K-MEANS DAN KMEDOIDS UNTUK KLASTERISASI DATA KEMISKINAN DI SUMATERA SELATAN MENGGUNAKAN EVALUASI DAVIES BOULDIN INDEX

---

Penilaian

---

This research focuses on the implementation and comparison of the KMeans and KMedoids algorithms that function as poverty data clustering in South Sumatra Province, the poverty data is taken from the Central Statistics Agency of Indonesia (BPS Indonesia). This research also aims to analyze the poverty level in South Sumatra Province by including additional variables such as average years of schooling and per capita expenditure in the community in each regency or city in South Sumatra Province. Data clustering is done by both algorithms and then the performance value is Evaluated using Davies Bouldin Index DBI shows that KMeans gives better results, with a lower DBI value (0.204 at K=5) while KMedoids has a DBI value of 0.239 at K=5, which indicates more compact and separated clusters. The superiority of K-Means is due to the homogeneous and minimal outlier characteristics of the dataset, which makes the centroid approach more optimal than medoids in K-Medoids. With these results, K-Means was chosen as the best algorithm for clustering poverty data in the region. The use of the KMeans algorithm produces a pattern in clusters related to education, economic inequality, and poverty distribution in various regions in South Sumatra. This implementation provides insight into how data clustering techniques can be applied to socioeconomic data to provide policy makers in a region with information about the region, especially information about poverty-stricken areas.

---

Availability

Inventory Code	Barcode	Call Number	Location	Status
2507000088	T162974	T1629742024	Central Library (Reference)	Available but not for loan - Not for Loan

Detail Information

Series Title

-

Call Number

T1629742024

Publisher

Indralaya : Prodi Sistem Informasi, Fakultas Ilmu Komputer., 2024

Collation

xv, 68 hlm.; ilus.; tab. 29 cm.

Language

Indonesia

ISBN/ISSN

-

Classification

518.107

Content Type

Text

Media Type

-

Carrier Type

-

Edition

-

Subject(s)

Prodi Sistem Informasi, Fakultas Ilmu Komputer
Perbandingan Algoritma

Specific Detail Info

-

Statement of Responsibility

MI

Other version/related

File Attachment

Comments

---

You must be logged in to post a comment