METODE PRINCIPAL COMPONENT ANALYSIS PADA FAKTOR-FAKTOR YANG MEMPENGARUHI KEMISKINAN PULAU SUMATERA
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Date
2022-04
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Elfitra
Abstract
Sumatera Island is the sixth largest island in the world, located in Indonesia, consisting
of 154 regencies/cities. Sumatra Island is ranked fourth in the Indonesia for having the
highest percentage of poor people, with 5,8 million in 2020. The factors that influence
poverty can be viewed from the fields of population, employment, health, education,
and the economy. The number of these factors can be reduced by using one of the
methods in multivariate analysis, namely Principal Component Analysis (PCA). PCA
aims to reduce data consisting of many variables that are interrelated with one another
but still maintain the largest possible variance from the original data. The variables used
to consist of 7 variables, namely, Open Unemployment Rate (𝑋1), Average Length of
Schooling (𝑋2), Expenditure Per Capita (𝑋3), Population Density(𝑋4), Total Population
(𝑋5), Gross Regional Domestic Product (𝑋6), and Life Expectancy(𝑋7). By using the
correlation matrix in PCA analysis, three principal components are obtained with a
cumulative proportion of variance of 77,8% in explaining the diversity of the original
variable.
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Keywords
Multivariate analysis, principal component analysis, correlation matrix, poverty
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