@phdthesis{digilib74338,
           month = {July},
           title = {DETERMINASI INDIKATOR DIMENSI INDEKS PEMBANGUNAN MANUSIA (IPM) TERHADAP PERTUMBUHAN EKONOMI PROVINSI RIAU},
          school = {UIN SUNAN KALIJAGA YOGYAKARTA},
          author = {NIM.: 18108010068 Fakhri Aldani Hadamean S},
            year = {2025},
            note = {Dr. Miftakhul Chori, S.Sos.I., M.S.I.},
        keywords = {Umur Harapan Hidup, Rata-rata Lama Sekolah, Harapan Lama Sekolah, Pendapatan Per Kapita, Laju Pertumbuhan Ekonomi, Riau, EViews},
             url = {https://digilib.uin-suka.ac.id/id/eprint/74338/},
        abstract = {The economic growth of Riau Province is highly dependent on the oil and gas (O\&G) sector. Fluctuations in oil and gas prices and production have a significant impact on the stability and pace of regional economic growth. A decline in global commodity prices or a decrease in oil and gas production can trigger an economic slowdown in Riau. One indicator that reflects this condition is the Human Development Index (HDI), which consists of the variables Life Expectancy (LE), Average Years of Schooling (AYS), Expected Years of Schooling (EYS), and Per Capita Income (PCI) in the regencies/cities of Riau Province. This study aims to analyze the factors that influence the economic growth rate of Riau Province. The data were analyzed using EViews 12 software to identify the relationships among these four variables. The research results show that the LE variable (X1) has a regression coefficient of 0.086550, the AYS variable (X2) is 0.091876, and the PCI variable (X4) is 0.594699, indicating that all three variables have a positive and significant effect on the growth rate of Gross Regional Domestic Product (GRDP) per capita. Meanwhile, EYS (X3), with a coefficient of 0.014621, shows a positive but not significant effect on the GRDP growth rate per capita. The Jarque-Bera normality test yields a probability value of 0.250714 ({\ensuremath{>}} 0.05), indicating that the model is normally distributed. The Adjusted R-squared value of 0.830508 shows that the model is able to explain 83.05\% of the variation in the economic growth rate variable.}
}