<![CDATA[ABSTRAK Penelitian ini bertujuan untuk menguji pengaruh Umur Harapan Hidup (UHH), Tingkat Pengangguran Terbuka (TPT), dan pertumbuhan ekonomi yang diproksikan melalui Produk Domestik Regional Bruto atas Dasar Harga Konstan (PDRB ADHK) terhadap Indeks Pembangunan Manusia (IPM) pada 15 provinsi di Indonesia selama periode 2021–2024. Penelitian menggunakan pendekatan kuantitatif eksplanatori dengan data sekunder berbentuk balanced panel yang terdiri atas 60 observasi. Analisis data dilakukan menggunakan EViews 13 melalui statistik deskriptif, estimasi Common Effect Model (CEM), Fixed Effect Model (FEM), Random Effect Model (REM), Uji Chow, Uji Hausman, Uji Lagrange Multiplier, uji diagnostik, uji parsial (t), uji simultan (F), dan koefisien determinasi. Hasil pemilihan model menunjukkan bahwa Common Effect Model (CEM) merupakan model terbaik. Secara parsial, UHH berpengaruh positif dan signifikan terhadap IPM dengan koefisien sebesar 1,051392 dan probabilitas 0,0000. Sebaliknya, TPT dan PDRB ADHK tidak berpengaruh signifikan terhadap IPM dengan nilai probabilitas masing-masing 0,8715 dan 0,9779. Secara simultan, ketiga variabel independen tidak berpengaruh signifikan terhadap IPM dengan probabilitas uji F sebesar 0,1070. Nilai R-squared sebesar 0,1023 menunjukkan bahwa model mampu menjelaskan 10,23% variasi IPM, sedangkan sisanya dipengaruhi oleh faktor lain di luar model penelitian. ABSTRAK This study examines the effects of Life Expectancy (LE), the Open Unemployment Rate (OUR), and economic growth, proxied by Gross Regional Domestic Product at Constant Prices (GRDP), on the Human Development Index (HDI) across 15 Indonesian provinces during the 2021–2024 period. An explanatory quantitative approach was employed using balanced panel data comprising 60 observations. Data were analyzed using EViews 13 through descriptive statistics, Common Effect Model (CEM), Fixed Effect Model (FEM), Random Effect Model (REM), Chow test, Hausman test, Lagrange Multiplier test, diagnostic tests, t-test, F-test, and coefficient of determination (R²). The model selection results identified the Common Effect Model (CEM) as the most appropriate estimation model. The partial test indicates that Life Expectancy has a positive and significant effect on HDI, with a coefficient of 1.051392 and a probability value of 0.0000. In contrast, the Open Unemployment Rate and GRDP have no significant effects on HDI, with probability values of 0.8715 and 0.9779, respectively. Furthermore, the F-test shows that the three independent variables do not simultaneously affect HDI (p = 0.1070). The R² value of 0.1023 indicates that the model explains 10.23% of the variation in HDI, while the remaining variation is influenced by other factors outside the research model.]]>
Copyrights © 2026
