Media of Computer Science
Vol. 1 No. 2 (2024): December 2024

Evaluation Of Fuzzy C-Means Method For District Clustering

Nasrullah, Asmaul Husnah (Unknown)
Fajar, Andi Muhammad (Unknown)
Taufiq, Muhammad Aqsha (Unknown)
Rahmat, Nuzulul (Unknown)
Adiba, Fhatiah (Unknown)

Article Info

Publish Date
31 Dec 2024

Abstract

This study analyses the use of Fuzzy C-Means algorithm to cluster districts in South Sulawesi based on the education level of the population. Two distinct groups were found with several districts falling into each group after 17 iterations to reach the optimal solution. The clustering results were visualised with a point spread graph. The Fuzzy C-Means algorithm was executed using Python with certain parameters. The research aims to improve the quality of education with proper resource allocation and identification of districts based on the highest education. The data used includes education indicators and district minimum wage. The results are expected to provide input for a more targeted education policy in South Sulawesi. Fuzzy C-Means algorithm is effective for analysing and clustering education data in education policy decision making.

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Journal Info
Media of Computer Science
Website

Abbrev

mcs

Publisher

CV. Digital Innovation

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science

Description

Media of Computer Science (MCS), a two times annually provides a forum for the full range of scholarly study . MCS focuses on advanced computational intelligence, including the synergetic integration of neural networks, fuzzy logic and eveolutionary computation, so that more intelligent system can ...