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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL ILMIAH MATEMATIKA DAN TERAPAN KOMPUTIKA - Jurnal Sistem Komputer Parameter: Journal of Statistics MULTIPLE: Journal of Global and Multidisciplinary Tadulako Science and Technology Journal Khazanah Journal: Economics, Muamalah dan Entrepreneurship
Rais
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Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Grouping Districts / Cities in Central Sulawesi Province Based on Poverty Indicators Using the Fuzzy Geographically Weighted Clustering -Artificial Bee Colony Method Nafiul Agristya; Rais; Iman Setiawan
Tadulako Science and Technology Journal Vol. 2 No. 2 (2022): Tadulako Science and Technology Journal
Publisher : LPPM Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/sciencetech.v2i2.17301

Abstract

Introduction: Poverty is the main problem that is the focus of attention of the government in Indonesia. In general, poverty is a person's inability to meet basic basic needs in every aspect of life. Cluster analysis is a solution to map this problem. Method: Fuzzy Geographically Weighted Clustering-Artificial Bee Colony (FGWC-ABC) is one clustering method that is an integration of classical fuzzy clustering methods and geodemographic elements. Artificial Bee Colony is a metaheuristic algorithm that is used as a global optimization to increase cluster accuracy. Artificial Bee Colony can efficiently and effectively solve various function optimization problems in various cases. Result and Discussion: The research results obtained 3 optimum clusters with each cluster characteristic relatively different based on poverty indicators. Cluster 1 with low poverty, cluster 2 with high poverty, and cluster 3 with moderate poverty. Conclusion: By using the IFV validity index, 3 optimum clusters were obtained with different characteristics of each cluster based on its indicators. Cluster 1 consists of three regencies/cities with low poverty status, cluster 2 consists of seven regencies/cities with high poverty status, and cluster 3 consists of six regencies/cities with moderate poverty status.
Co-Authors Abdul Basit Agus Mohamad Soleh Andi Ferosita Sustrisno Andi Hendra Syam Budi Susetyo Fadjriyani Fajri, M Fiskia, N Gamayanti, Nurul Fiskia Hartayuni Sain Imam Hanafi Iman Setiawan Jamidun Jassinca Chrissma Audina Krisdianto, A H Lilies Handayani Maliku, E T Mohammad Fajri Musnar Indra Daulay Nafiul Agristya Nur'Eni Nursyahraini Husen Sain, H Setiawan, Iman Suryanto, Wiwit Very Kurnia Bakti, Very Kurnia