Klasterisasi Tingkat Kemiskinan di Indonesia menggunakan Algoritma K-Means
Assyifa Khalif,
Anisa Nur Hasanah,
Muhammad Hafizh Ridwan
et al.
Abstract:Poverty is one of the deep social challenges around the world and is a major focus in the global development agenda. This article discusses the role of clustering methods in analyzing and understanding poverty issues. We use data from Statistics Indonesia (BPS) on 34 provinces in Indonesia to classify groups of people who are vulnerable to poverty. Clustering analysis helps us identify characteristics that may be overlooked by conventional approaches, which in turn enables the development of more targeted and … Show more
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