Pengelompokan Provinsi di Indonesia Menggunakan Gaussian Mixture Model Berdasarkan Indikator Kemiskinan
Year: 2024
Type: article
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.
Institution: Universitas Jambi
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4403547318