Structural Equation Model (SEM) dalam Pemodelan Kemiskinan di Pulau Sumatera

Hasrat Ifolala Zebua, Geni Andalria Harefa


Poverty is a serious issue that must be addressed immediately by countries in the world, including Indonesia. The Indonesian government has implemented a variety of poverty reduction projects, such as providing education and health insurance. The rising poverty rate is due to the poor quality of education and health care. On Sumatra, there are 5,83 million poor people or 22,06 percent of the total number of poor people in Indonesia. This statistic appears to be quite large, and the government should be concerned about it. Factors causing poverty such as education and health are latent variables that cannot be measured directly. The suitable statistical method used is Structural Equation Model (SEM). In SEM analysis, there are three types of model fit tests: measurement model fit with Confirmatory Factor Analysis (CFA), overall model fit, and structural model fit. The results indicated that the model was fit or suitable for the model's tests. From the SEM model that was formed, it was found that health had a negative and significant effect on poverty and education did not have a significant effect on poverty and 77 percent of the variation in poverty could be explained by the SEM model that was formed.

Keywordspoverty; education; health; SEM; CFA

Full Text:



C. Suryawati, "Memahami Kemiskinan Secara Multidimensional," Jurnal Manajemen Pelayanan Kesehatan, vol. 8, no. 03, 2005.

S. H. Wijayanto, Structural Equations Modeling dengan Lisrel 8.8 Konsep dan Tutorial, Yogyakarta: Graha Ilmu, 2008.

BPS, Data dan Informasi Kemiskinan Kabupaten/Kota 2020, Jakarta: Badan Pusat Statistik, Jakarta, 2020.

M. Kuncoro, Ekonomi Pembangunan: Teori, Masalah dan Kebijakan, Yogyakarta: UPP AMP YKPN, 2006.

A. N. Ngafiyah dan B. W. Otok, "Meta-Analityc Structural Equation Modeling (MASEM) Pada Faktor-Faktor yang Mempengaruhi Kemiskinan di Pulau Jawa," Prosiding Seminar Nasional Matematika, Universitas Jember, vol. 1, no. 1, 2014.

E. D. Anggita, A. Hoyyi and A. dan Rusgiyono, "Analisis Structural Equation Modelling Pendekatan Partial Least Square dan Pengelompokan dengan Finite Mixture PLS (FIMIX-PLS) (Studi Kasus: Kemiskinan Rumah Tangga di Indonesia 2017)," Jurnal Gaussian, vol. 8, no. 1, pp. 35 – 45, 2019.

M. Artati, Y. Supiyadi dan Y. Suparman, "Multigroup Structural Equation Models (SEM) Data Kemiskinan Indonesia," Prosiding Seminar Nasional Statistika IV, Universitas Padjadjaran, 2014.

K. A. Bollen, Structural Equations with Latent Variables, Department of Sociology, New York: John Wiley and Sons, 1989.

L. Hortensius, Project for Introduction to Multivariate Statistics: Measurement Invariance, 2012.

D. Iacobucci, "Structural Equations Modeling: Fit Indices, Sample Size and Advanced Topics," Journal of Consumer Psychology, vol. 20, pp. 90-98, 2009.

J. Hair, W. Black, B. Babin and R. Anderson, Multivariate Data Analysis, Sixth Edition, New Jersey: Pearson International Edition, 2007.

A. Diamantopoulus and J. A. Siguaw, Introducing Lisrel: A Guide for the Uninitiated, London: Sage Publications, 2013.

R. Dodd and L. Munck, Dying for Change: Poor People’s Experience of Health and Health, World Health Organization, World Bank, 2002.


  • There are currently no refbacks.