BAREKENG: Jurnal Ilmu Matematika dan Terapan
Vol 14 No 3 (2020): BAREKENG: Jurnal Ilmu Matematika dan Terapan

A COMPARISON OF CENTRALITY MEASURES IN SUSTAINABLE DEVELOPMENT GOALS

Sena Ariesandy (Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran)
Ema Carnia (Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran)
Herlina Napitupulu (Universitas Padjadjaran)



Article Info

Publish Date
01 Sep 2020

Abstract

The Millennium Development Goals (MDGs), which began in 2000 with 8 goal points, have not been able to solve the global problems. The MDGs were developed into Sustainable Development Goals (SDGs) in 2015 with 17 targeted goal points achieved in 2030. Until now, methods for determining the priority of SDGs are still attractive to researchers. Centrality measure is one of the tools in determining the priority goal points on a network by using graph theory. There are four measurements of centrality used in this paper, namely degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. The calculation results obtained from the four measurements are compared dan analyzed, to conclude which goal points are the most prior and the least prior. Furthemore, in this paper we present other example with simple graph to show that each different centrality calculation possibly resulted different priority node, the calculation of this illustration is done using a Python’s library named NetworkX

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Journal Info

Abbrev

barekeng

Publisher

Subject

Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

Description

BAREKENG: Jurnal ilmu Matematika dan Terapan is one of the scientific publication media, which publish the article related to the result of research or study in the field of Pure Mathematics and Applied Mathematics. Focus and scope of BAREKENG: Jurnal ilmu Matematika dan Terapan, as follows: - Pure ...