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kholijah, gusmi
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Journal : Journal of Mathematics: Theory and Applications

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Pengelompokan Provinsi di Indonesia Menggunakan Gaussian Mixture Model Berdasarkan Indikator Kemiskinan Alyarahma, Nyimas Nina; Kholijah, Gusmi; Sormin, Corry
Journal of Mathematics: Theory and Applications Vol 6 No 2 (2024)
Publisher : Program Studi Matematika Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31605/jomta.v6i2.4032

Abstract

Poverty is a multidimensional concept that can not only be seen from an economic perspective, but can also be seen from a social, cultural and political perspective. Poverty is generally expressed as a static concept with the amount of poverty as a description of welfare conditions at a certain time. In reality, poverty has a time period that is never cut off and has a continuous pattern over time. The Indonesian government is committed to efforts to eradicate poverty in order to reduce Indonesia's poverty rate. One way that can be done is by allocating aid to the community. Grouping is carried out by cluster analysis using the Gaussian Mixture Model method with the Expectation-Maximization (EM) algorithm. The optimal number of clusters in the Gaussian Mixture Model uses the Bayesian Information Criterion (BIC) method. Based on the research carried out, the results of the analysis of cluster grouping using the Gaussian Mixture Model method were obtained with the smallest BIC value, namely -397.6876 with a total of 2 clusters.
Co-Authors Alim, Khairul Alyarahma, Nyimas Nina Amelia, Dwi Gusmanely.Z, Gusmanely.Z Ivone Damanik, Ellys M. RIZKY RAMADHAN Mardhotillah, Bunga Meinarisa, Meinarisa Mubarak, Hosni Multahadah, Cut rarasati, niken Safitri, Yuliana Sarmada, Sarmada Sinaga, Ira Selvia Sormin, Corry Sri Rezeki, Elizabet Sufri Sufri Tanjung, Kartika Anjalya Tasmara, Annida Tasya, Anisya Wardi Syafmen Yurinanda, Sherly Z, Gusmanely