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All Journal Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population)
Hardian Bimanto
Faculty of Public Health, Universitas Airlangga, 60115 Surabaya, East Java, Indonesia

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APPLICATION OF THE PRAIS WINSTEN METHOD IN OVERCOMING AUTOCORRELATION ON LIFE EXPECTATION FACTORS Hardian Bimanto; Hari Basuki Notobroto; Soenarnatalina Melaniani
Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population) Vol. 12 No. 1 (2023): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v12i1.2023.32-40

Abstract

One of the error conditions that are required to be met is the absence of autocorrelation problems. Autocorrelation is a correlation of errors between observations, the existence of an error correlation between observations will cause deviations from the actual statistical value. One of the statistical methods for overcoming autocorrelation is the Prais Winsten method. This study aims to explain the Prais Winsten method in overcoming the problem of autocorrelation on factors that affect the life expectancy of East Java Province in 2018. This research is a secondary data analysis, data obtained from the East Java Province's health profile in 2018 with the dependent variable, namely life expectancy, and independent variables, namely prevalence of diarrhea, clean and healthy living behavior, and mean years of school. The results of this research indicated the finding of autocorrelation problems in the factors that affected the life expectancy of East Java Province in 2018. Improvements with the Prais Winsten method showed that the Durbin Watson value was at the critical point limit, Mean Square Error and coefficient of determination (R2) value was decreasing. This research concludes that the Prais Winsten method can overcome autocorrelation.
Co-Authors Hari Basuki Notobroto Soenarnatalina Melaniani