MENGANALISIS PENGARUH KEMISKINAN DI PROVINSI RIAU DENGAN METODE ANALISIS REGRESI LINEAR BERGANDA DAN DATA PANEL

Sarbaini Sarbaini; Fara Ulfa

doi:10.24260/add.v2i2.1835

Sarbaini Sarbaini Universitas Islam Negeri Sultan Syarif Kasim Riau
Fara Ulfa Universitas Islam Negeri Sultan Syarif Kasim Riau

DOI: https://doi.org/10.24260/add.v2i2.1835

Abstract

Poverty is a state of being unable to meet basic human needs such as food, clothing, shelter, education, and health. The poverty rate can be influenced by population, employment, and unemployment. Moreover, the world's economic conditions are changing from time to time, requiring humans to survive in every situation. The poverty research conducted in Riau Province requires large data and data management, and the data used uses time series data. The data used in this research is secondary data obtained from the official website of the Indonesian Central Bureau of Statistics. This study aims to determine the effect of poverty in Riau Province in 2018-2021 and compare the two methods used to analyze this research. The two methods used in this study are Panel Data Regression which includes Common Effect Model (CEM), Fixed Effect Model (FEM), Random Effect Model (REM), and Multiple Linear Regression. The study results show that the panel data linear regression method is the most appropriate for data on the influence of poverty in Riau Province in 2018-2021.

References

Borenstein, M., Hedges, L. V, Higgins, J. P. T., & Rothstein, H. R. (2010). A basic introduction to fixed‐effect and random‐effects models for meta‐analysis. Research Synthesis Methods, 1(2), 97–111.
Geisser, S. (1974). A predictive approach to the random effect model. Biometrika, 61(1), 101–107.
Kuncoro, S., & Riyardi, A. (2014). Analisis pengaruh pertumbuhan ekonomi, tingkat pengangguran dan pendidikan terhadap tingkat kemiskinan di provinsi jawa timur tahun 2009-2011. Universitas Muhammadiyah Surakarta.
Muda, I., Sidauruk, H., & Siregar, H. S. (2018). The Effect of Corporate Social Responsibility on Company’s Value with Common Effects Model (CEM), Fixed Effects Model (FEM) and Random Effects Model (REM) Approaches (Empirical Evidence in Indonesia Stock Exchange). Quality-Access to Success, 19(165).
Nandita, D. A., Alamsyah, L. B., Jati, E. P., & Widodo, E. (2019). Regresi data panel untuk mengetahui faktor-faktor yang mempengaruhi PDRB di Provinsi DIY tahun 2011-2015. Indonesian Journal of Applied Statistics, 2(1), 42–52.
Pace, R. K., & LeSage, J. P. (2008). A spatial Hausman test. Economics Letters, 101(3), 282–284.
Toyoda, T. (1974). Use of the Chow test under heteroscedasticity. Econometrica: Journal of the Econometric Society, 601–608.
Yacoub, Y. (2012). Pengaruh Tingkat Pengangguran terhadap Tingkat Kemiskinan Kabupaten / Kota di Provinsi Kalimantan Barat. 8, 176–185.