CD Skripsi

Pemodelan Jumlah Penduduk Miskin Di Indonesia Menggunakan Geographically Weighted Negative Binomial Regression

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ABSTRACT
Poverty is a condition of an individual’s inability to meet his basic needs. The
number of poor people in Indonesia in September 2019 was 24,79 million people
or around 9,22%. This study uses a geographically weighted negative binomial
regression model to determine the factors that affect the amount of poverty in
Indonesia in 2019. Modeling the number of poor people in Indonesia using
Poisson regression is overdispersed, so to overcome it using geographically
weighted negative binomial regression. Based on the regression model used, the
results show that the significant variables are the open unemployment rate, the
percentage of households that occupy non-private houses, the percentage of
illiteracy, and gross regional domestic product at current prices per capita.
Keywords: Poverty, geographically weighted negative binomial regression,
Poisson regression, overdispersion, negative binomial regression.

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

03 06. 121 (0003)

Penerbit

Pekanbaru : Universitas Riau – FMIPA – Statistika., 2021

Deskripsi Fisik

ix, 79 hlm.; ill.: 29 cm

Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

03 06. 121 (0003)

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

STATISTIKA

Info Detail Spesifik

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Pernyataan Tanggungjawab

ELFITRA

Versi lain/terkait

Lampiran Berkas

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