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All Journal Rekursif: Jurnal Informatika
Ahmad Saputra, Fahim
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Analisis Klaster Negara Berdasarkan Indikator Sosial-Ekonomi Menggunakan Fuzzy C-Means dan K-Means Sulaiman, Davi; Afrian Al-Haritz, Rafi; Ahmad Saputra, Fahim; Irawan, Ade
Rekursif: Jurnal Informatika Vol 12 No 2 (2024): Volume 12 Nomor 2 November 2024
Publisher : Universitas Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/rekursif.v12i2.38116

Abstract

This paper analyzes country clustering based on socio-economic indicators using Fuzzy C-Means (FCM) and K-Means algorithms. Each country has unique socio-economic characteristics that include aspects such as child mortality, exports, imports, per capita income, inflation, life expectancy, and gross domestic product. The dataset used includes 167 countries with 10 key indicators. After pre-processing and normalizing the data, clustering is performed using FCM and K-Means, where effectiveness is evaluated based on Sum of Squared Errors (SSE) and Silhoutte Score. This research aims to find the best algorithm in terms of accuracy and time efficiency in clustering countries based on socio-economic indicators. Keywords: Clustering, Fuzzy C-Means, K-Means, Socio-economic indicators, Sum of Squared Errors (SSE), Silhouttte Score.
Co-Authors Ade Irawan Afrian Al-Haritz, Rafi Sulaiman, Davi