Analysis of the Influence of Average School Length, Per Capita Expenditure, and Life Expectancy on the Human Development Index in West Nusa Tenggara Province in 2019-2023

Studies Management and Finance Economics, of Journal 0504-2644 (online): ISSN 0490,-2644 (print): ISSN 5202 October 10 Issue 80 Volume 8.317 Factor: Impact ,38-i10-10.47191/jefms/v8 DOI: Article 9546 -6944 No: Page JEFMS, Volume 08 Issue 10 October 2025 www.ijefm.co.in Page 6944 Analysis of the Influence of Average School Length, Per Capita Expenditure, and Life Expectancy on the Human Development Index in West Nusa Tenggara Province in 2019-2023 M. Ilham Anang Kurniawan1, St. Maryam2 1,2Faculty of Economics and Business, University of Mataram, Indonesia ABSTRACT: The purpose of this study is to analyze the influence of Average School Length, Per Capita Expenditure, and Life Expectancy on the Human Development Index in West Nusa Tenggara Province in 2019-2023. The research method used was multiple linear regression with the Fixed Effect Model model and the type of associative quantitative research. This study uses secondary data that already exists at the Central Statistics Agency of West Nusa Tenggara Province by using panel data for five years starting from 2019-2023. Data processing is carried out with the help of software in the form of Eviews 12. Based on these objectives, the results of the study show that the Average School Length partially has a positive and significant influence on the Human Development Index. Per Capita Expenditure partially has a negative but significant influence on the Human Development Index. Meanwhile, life expectancy partially has a positive but not significant effect on the Human Development Index in districts/cities of West Nusa Tenggara Province in 2019-2023. However, the Average School Length, Per Capita Expenditure, and Life Expectancy simultaneously and significantly affect the Human Development Index in the districts/cities of West Nusa Tenggara Province in 2019-2023. KEYWORDS: Average School Length, Per Capita Expenditure, Life Expectancy, Human Development Index I. INTRODUCTION Indonesia is an archipelagic country consisting of 38 provinces and each province has its own characteristics as a result of geographical differences. The existence of geographical differences is a big challenge for the government to carry out equitable development on a national scale. Meanwhile, the goal of national development is to improve the standard of living of the community in aggregate, one of which is human development. According to Central Statistics Agency (2021), the Human Development Index is a composite index used to assess the development of the quality of human life. The measure in the assessment of the success of human builders is the human development index. According to (UNDP, 2020 in Yeni Yulianti & Siti Qomariah, 2025) Human development does not only focus on material or economic aspects, but also from social, educational, and health aspects. The difference in geographical location and uneven development causes the difference in the Human Development Index in each province in Indonesia to be a very crucial issue and requires special attention. Provinces in the western part of Indonesia tend to have a high Human Development Index, in contrast to provinces in the eastern part of Indonesia tend to have a lower Human Development Index. One of the provinces that has a Human Development Index below the national Human Development Index average is West Nusa Tenggara Province. The average national Human Development Index recorded in 2023 is 73.55. The trend of the West Nusa Tenggara Province Human Development Index can be seen in Table.1 below. Table 1. West Nusa Tenggara Province Human Development Index Regency/City Human Development Index (HDI) 2019 2020 2021 2022 2023 West Lombok 68.03 70.23 70.64 71.44 72.18 Central Lombok 66.36 68.32 68.70 69.57 70.41 Analysis of the Influence of Average School Length, Per Capita Expenditure, and Life Expectancy on the Human Development Index in West Nusa Tenggara Province in 2019-2023 JEFMS, Volume 08 Issue 10 October 2025 www.ijefm.co.in Page 6945 East Lombok 66.23 68.54 68.90 69.83 70.65 Sumbawa 67.60 69.43 69.82 70.71 71.68 Dompu 67.83 69.65 70.27 70.96 71.77 Bima 66.37 68.36 68.72 69.63 70.33 West Sumbawa 71.52 73.34 73.54 74.34 74.84 North Lombok 64.49 65.80 66.14 67.09 68.02 Mataram City 79.10 80.02 80.24 80.67 81.15 Bima City 75.80 76.74 77.03 77.75 78.24 West Nusa Tenggara 68.14 70.46 70.86 71.65 72.37 Source: Central Statistics Agency of West Nusa Tenggara 2024 Based on the table. 1 The West Nusa Tenggara Province Human Development Index increased in 2020 by 2.32 to 70.46 which initially in 2019 was at 68.14. In 2021 it increased again by 0.4 which became 70.86, the rate of increase in the Human Development Index was lower than in 2020 this was due to the influence of the Covid-19 pandemic that hit Indonesia, especially in West Nusa Tenggara Province. In 2022 it increased by 0.79 to 71.65, this figure has increased significantly compared to 2021, while in 2023 the increase in the Human Development Index figure is lower than in 2022, which is 0.72 and in 2023 the Human Development Index figure reaches 72.37. Although the Human Development Index of West Nusa Tenggara Province has increased every year, the growth rate tends to be slower compared to other provinces in Indonesia. In this context, it shows that there is a fault or obstacle in improving the quality of education, income, and validity which is the most important component in the human development index. Based on geographical location, West Nusa Tenggara Province has two main islands, namely Lombok Island and Sumbawa Island, both islands have different characteristics. In remote areas, people's access to education and health aspects is still very limited, so in this case it has an impact on the achievement of human development indicators. The limitations of infrastructure, the distance traveled, and the limitation of professionals are a real challenge for the equitable distribution of development in West Nusa Tenggara Province. The average length of school in West Nusa Tenggara Province in 2023 was recorded at 7.74 (years) which shows that the average person only takes education until grade VII junior high school or equivalent. This figure is lower when compared to the national average which is at 8.77 (years) judging from data in 2023. With the low average number of school years, it can be one of the inhibiting factors in improving existing human resources. Because with low education, it can affect the limitations of skills and competitiveness in the world of work. In addition to the low average length of schooling, the per capita expenditure of West Nusa Tenggara Province is also relatively low when compared to other provinces in Indonesia. The existence of limited income will have an impact on people's limited purchasing power, such as the aspect of meeting basic needs, the education aspect, and even the health aspect. The low purchasing power of the community will affect the inhibition of progress in human development caused by people who are less able to get access to services and facilities needed to improve the quality of life. In terms of health, the Life Expectancy in West Nusa Tenggara Province in 2023 was recorded at 72.02 (years) but was slightly below the national average of 72.13 (years) in 2023. The low life expectancy in West Nusa Tenggara Province is influenced by several determinants, including the lack of health facilities, the existence of an unhealthy lifestyle, and even the nutritional level of the community that has not reached optimal. Low life expectancy has an influence on the low health aspect of the Human Development Index. The three variables above, namely Average School Age, Expenditure Per Capita, Life Expectancy, are the most important elements in the formation of the Human Development Index. A significant increase in one of these variables will not guarantee that the Human Development Index will increase significantly. Therefore, to improve the Human Development Index, an approach is needed that can simultaneously improve these three variables so that they have a sustainable impact. In the 2019-2023 period, the focus of this study is because it covers the occurrence before and after the occurrence of Covid19. The existence of the pandemic has had a great effect on education, economy, and health. The closure of learning activities, both in schools and campuses, which lasts for quite a long time, has an impact on the results of the Average School Length, the existence of delays in the economic field can affect people's per capita expenditure, and limited mobility affects access to health services and life expectancy. Analysis of the Influence of Average School Length, Per Capita Expenditure, and Life Expectancy on the Human Development Index in West Nusa Tenggara Province in 2019-2023 JEFMS, Volume 08 Issue 10 October 2025 www.ijefm.co.in Page 6946 Based on the theory of human development put forward by Amartya Sen, the concept of "capability" development as ( Michael P. Todaro, 2003:24 in Indarti, 2017) freedom that a person has in the sense of choice Functioning, in his personal aspect (a change in characteristics to Functioning) and have control over commodities. In this case, the emphasis on improving the quality of life is not only dependent on economic aspects, but also the development of individual abilities. In the aspect of education through the Average School Length can expand the knowledge and skills possessed by the community, the income reflected in the per capita expenditure of the community can meet its basic needs, and the aspect of health measured through Life Expectancy has an influence on prolonging a healthy life. The three variables above are in line with the concept of human development in aggregate. Based on the results of previous research conducted by Dastanta Irvan Ginting and Irsad Lubis (2023), the data analysis method used was a multiple linear regression model with the Ordinary Least Square method. The results of the study showed a positive correlation between life expectancy and the Mansia Development Index, which confirmed that the increase in life expectancy correlated with the increase in the Human Development Index. This phenomenon reflects the positive impact of improving public health on overall human development. Furthermore, school age has also been shown to play an important role in shaping the Human Development Index. The results of the analysis showed that people with higher school years tended to have a higher Human Development Index. This illustrates the close relationship between formal education investment and increased levels of human development. This research provides valuable insights into the driving factors for sustainable human development in the context of Lalat Regency. Arif, Dzaki Ade Alfarez, M. Rizky Ramadhan, Bunga Mardhotillah (2023), the method used is multiple linear regression analysis in JESP software. The results of the research from the results of the study found that Life Expectancy, School Length of Expectancy, and Average School Length have an influence on the Human Development Index if they are influenced together (simultaneously). Life Expectancy can also independently affect the Human Development Index, but for the Average School Expectancy and Average School Age cannot affect the Human Development Index individually. The limitations of previous researchers can be used as a very important opportunity to conduct a more in-depth analysis, where in this context it is very necessary to link between, Average School Age, per capita expenses, and Life Expectancy in one research framework. This approach can be used as an evaluation material for how much each variable has an impact on the Human Development Index in West Nusa Tenggara Province in 2019-2023. Based on the description above, the formulation of the problem in this study is: • Does Average School Length, Per Capita Expenditure, and Life Expectancy Affect the Human Development Index in West Nusa Tenggara Province in 2019-2023? Based on the formulation of the problem above, the purpose of this study is to analyze the influence of Average School Length, Expenditure per Capita, and Life Expectancy on the Human Development Index in West Nusa Tenggara Province in the 2019-2023 period. The benefit of this research in the academic field is as a reference by the next researcher so that this research becomes sustainable, while for the government it is to provide data-based recommendations for local and central governments in formulating policies related to human development that are more effective and on target. This research not only contributes in the academic field but also practical benefits in encouraging the improvement of the Human Development Index and reducing the gap in human development in West Nusa Tenggara Province. II. LITERATURE REVIEW A. Human Development Index Squirt United Nations Development Programme deep Todaro & Smith (2011), the Human Development Index is a ranking system for countries with a value limit of 0 (lowest human development) to 1 (highest human development). This ranking is based on three aspects of development: life expectancy, which is measured from the average age after birth; knowledge, which is assessed from the average literacy rate and school participation ratio; and standard of living, which is calculated using gross domestic product per capita that has been adjusted for purchasing power. B. Average School Length United Nations Development Programme deep Todaro & Smith (2011), in the latest Human Development Index, there are improvements in the education aspect, where two new components are added. These components are the average actual educational attainment of the population and the expected educational attainment of children today. Each of these changes shows a significant improvement with the use of the Average School Length as an indicator of the level of educational achievement. According to Central Statistics Agency (2024), Average School Length is the average number of years spent by residents aged 15 years and above in pursuing various levels of education. In this context, the higher the level of education a person gets, the more Analysis of the Influence of Average School Length, Per Capita Expenditure, and Life Expectancy on the Human Development Index in West Nusa Tenggara Province in 2019-2023 JEFMS, Volume 08 Issue 10 October 2025 www.ijefm.co.in Page 6947 skills and productivity he or she has. This makes competitiveness also increase, thus contributing to the increase in the Human Development Index. C. Per Capita Expenditure According to Department of Industry and Trade (2024), per capita expenditure is the total cost incurred for consumption by all household members in a month, divided by the number of family members adjusted for purchasing power. According to the United Nations Development Programme, living standards are measured based on gross domestic product per capita which has been adjusted for the purchasing power parity of the currency value of each different country to reflect the cost of living assuming that marginal utilities are decreasing. However, in Indonesia, the Central Statistics Agency chose not to use Gross National Income per capita as a measure of living standards in the calculation of the regional Human Development Index. Instead, the Central Statistics Agency uses adjusted real per capita expenditure. This is due to the difficulty of obtaining data Gross National Income per capita at the provincial or city/district level. On the other hand, per capita expenditure is more accurate in representing people's purchasing power at the regional level (BPS, 2024). Therefore, the better the standard of living of the community, the Human Development Index will increase. D. Life Expectancy Life Expectancy is the estimated average age that a person can reach from birth, based on mortality patterns that are considered to be constant throughout his or her life (Rodiyah et al., 2025). This Life Expectancy figure reflects the quality of health services obtained by the community. The higher the Life Expectancy, the better the health services received. The high figure shows that there is significant progress in the health sector in the context of the Human Development Index. Hypotheses and Conceptual Frameworks Hypothesis It is suspected that the average length of schooling, Expenditure Per Capita, and Life Expectancy have a positive and significant effect on the Human Development Index of West Nusa Tenggara Province. Conceptual Framework Table 1. Conceptual Framework Table 1. shows how the influence of independent variables on dependent variables, both partially and simultaneously, in this case the variables Average School Length (X1), Expenditure Per Capita (X2), and Life Expectancy (X3) on the variables of the Human Development Index (Y). III. METHODOLOGY The type of research used is associative quantitative. According to (Kasiram, 2008 in Karimuddin et al., 2022) associative is a study to see the relationship between variables. This study uses secondary data that already exists at the Central Statistics Agency of West Nusa Tenggara Province by using panel data for five years starting from 2019 to 2023. The data analysis method used in this study is multiple linear regression analysis with the help of software eviews 12. Multiple linear regression itself is a model in regression using more than one independent variable (Nastiti & Nailufar, 2024). The equations used in this study are as follows: Yit = β0 + β1X1it + β2X2it + β3X3it + Ɛit Average School Length (X1) Per Capita Expenditure (X2) Life expectancy (X3) Human Development Index (Y) Analysis of the Influence of Average School Length, Per Capita Expenditure, and Life Expectancy on the Human Development Index in West Nusa Tenggara Province in 2019-2023 JEFMS, Volume 08 Issue 10 October 2025 www.ijefm.co.in Page 6948 Information: Y : Human Development Index X1 : Average School Length X2 : Per Capita Expenditure X3 : Life expectancy β0 : Constant β1, β2, β3 : Regression Coefficient Value Ɛ : Error i : Cross Section t : Time Series A. Classic Assumption Test In testing classic assumptions on panel data, not everything has to be done. Linearity testing is not performed because it is assumed that the model is already linear. In addition, normality testing is also not necessary because it is basically not a requirement Best Linear Unbias Estimator and in some approaches it is not required. In autocorrelation testing, only data is performed Time series and no testing was carried out on the data cross section and panel data (Ningrum et al., 2020). Meanwhile, panel data is very necessary for multicollinearity testing because it aims to test whether in the regression model there is a high or even perfect correlation on independent variables, while the heteroscedasticity test aims to test whether in the regression model there is variance disparity from residual in one observation to another (Ghazali, 2013 in Ningrum et al., 2020). Therefore, the classical assumption test used is the multicollinearity test and the heteroscedasticity test. Multicollinearity Test The multicollinearity test is a test that is carried out to see if the existing regression equations contain independent variables that are related to each other. A regression model that does not occur multicollinearity is a model that has a coefficient between independent variables with a value of < 0.90 while with a coefficient value between independent variables > 90, multicollinearity occurs (Choirunnisa, 2017 in Arin Ramadhiani Soleha & Moh. Faizin, 2023). Heteroscedasticity Test The heteroscedasticity test is a test that aims to see whether in the regression equation there is a dissimilarity of residual variants in one observation with another observation (Ghozali, 2012 in Nastiti & Nailufar, 2024). B. Statistical Test Partial Test (t-test) Partial test (t-test) is a test that is carried out to see how much influence each independent variable has on the dependent variable. If the probability value > 0.05 then the variable does not have a significant effect, but if the probability value is < 0.05, then the variable has a significant effect. Simultaneous Test (F-Test) Simultaneous testing (F-test) is an exam that aims to see how much influence all independent variables have on the dependent variables. The test is seen from the value of the probability significance of the F-Statistic, if the probability (F-Statistic) < 0.05, then simultaneously the independent variable affects the dependent variable, if the probability (F-Statistic) > 0.05, then the independent variable simultaneously does not affect the dependent variable. Coefficient of Determination Test (R2) Determination coefficient test (R2) is a test that aims to see the effect of independent variables on the change of dependent variables. If the value of the coefficient of determination is close to the number 0, the effect is very limited, but if the value of the coefficient of determination is close to the number 1, the influence is stronger (Arin Ramadhiani Soleha & Moh. Faizin, 2023). IV. RESULTS AND DISCUSSION Panel Data Regression Modeling Chow Test Table 1. Chow Test Results Test Prob. Chow Test 0.0000 Source: Eviews Data Processing Results 12 Analysis of the Influence of Average School Length, Per Capita Expenditure, and Life Expectancy on the Human Development Index in West Nusa Tenggara Province in 2019-2023 JEFMS, Volume 08 Issue 10 October 2025 www.ijefm.co.in Page 6949 In Table 1. is the result of testing in the CHOW test where the probability value is 0.0000 < 0.05 which means that the chosen model is the Fixed Effect Model. When the model selected in the chow test is the Fixed Effect Model, it is necessary to retest it with a thirst test to see if the Fixed Effect Model is the best model used in this study. Hausman Test Table 2. Hausman Test Results Test Prob. Hausman Test 0.0000 Source: Eviews Data Processing Results 12 In Table 2. is the result of the Hausman test which shows a probability value of 0.0000 < 0.05 which means that the selected model is the Fixed Effect Model. Based on the test results of Table 2. it can be concluded that the selected model is the Fixed Effect Model without performing the Lagrange Multiplier test because the one selected in the thirst test is the Fixed Effect Model model. This is supported by the research conducted (Sari & Warsitasari, 2023), the results of the chow and hausman tests selected for the Fixed Effect Model model, therefore the Lagrange Multiplier test was not carried out. Based on the results of the panel data regression test by testing the model specifications, the best model was obtained was the Fixed Effect Model. The results of data processing can be seen in Table 3. below. Table 3. Results of Data Regression Panel Fixed Effect Model Dependent Variable: Y Method: Panel Least Squares Date: 09/21/25 Time: 08:32 Sample: 2019 2023 Periods included: 5 Cross-sections included: 10 Total panel (balanced) observations: 50 Variable Coefficient Std. Error t-Statistic Prob. C 27.98865 4.355259 6.426403 0.0000 X1 5.361404 0.882468 6.075464 0.0000 X2 -0.001350 0.000638 -2.115541 0.0412 X3 0.219693 0.110089 1.995596 0.0534 Effects Specification Cross-section fixed (dummy variables) Root MSE 0.601728 R-squared 0.980201 Mean dependent var 71.38040 Adjusted R-squared 0.973780 S.D. dependent var 4.319872 S.E. of regression 0.699495 Akaike info criterion 2.341979 Sum squared resid 18.10385 Schwarz criterion 2.839105 Log likelihood -45.54947 Hannan-Quinn crister. 2.531287 F-statistic 152.6521 Durbin-Watson stat 1.922512 Prob(F-statistic) 0.000000 Source: Eviews Data Processing Results 12 Based on the results of the panel data regression using the Fixed Effect Model approach, the following equations were obtained. Y = 27.9886498947 + 5.36140406151X1 - 0.00134955333532X2 + 0.219692639077X3 Information: Y : Human Development Index Analysis of the Influence of Average School Length, Per Capita Expenditure, and Life Expectancy on the Human Development Index in West Nusa Tenggara Province in 2019-2023 JEFMS, Volume 08 Issue 10 October 2025 www.ijefm.co.in Page 6950 β0 : Constant X1 : Average School Length X2 : Per Capita Expenditure X3 : Life expectancy The interpretation based on the above model is as follows: a. The constant value (β0) is positive, which is 27.9886498947, which means that if the variables of Average School Length (X1), Expenditure Per Capita (X2), and Life Expectancy (X3) are 0 (zero), then the Human Development Index variable (Y) has increased by 27.98. b. The value of the regression coefficient of the Average School Length variable (X1) is positively marked as b1 = 5.36140406151, meaning that the value shows a direct relationship if the Average School Length variable increases by 1 percent, it will cause an increase in the Human Development Index variable of 536.14 percent using the assumption that the other variables are constant. c. The value of the regression coefficient of the Per Capita Expenditure variable (X1) is negatively marked as b2 = - 0.00134955333532 meaning that the value shows an indirect relationship if the Per Capita Expenditure variable increases by 1 percent, it will cause a decrease in the Human Development Index variable by 0.13 percent using the assumption that the other variables are constant. d. The value of the regression coefficient of the Life Expectancy variable (X3) is positively marked as b3 = 0.219692639077 meaning that the value shows a unidirectional relationship if the Life Expectancy variable increases by 1 percent, it will cause an increase in the Human Development Index variable of 21.96 percent using the assumption that the other variables are constant. A. Classic Assumption Test Multicollinearity Test Table 4. Multicollinearity Test Results X1 X2 X3 X1 1 0.4355300979871607 0.5748399902331901 X2 0.4355300979871607 1 0.6383277518762344 X3 0.5748399902331901 0.6383277518762344 1 Source: Eviews Data Processing Results 12 In the testing Table 4. Data multicollinearity, a tolerable correlation value below 0.90 which means that based on the results of the multicollinearity test above, there is no correlation value for each independent variable because < 0.90 then it is stated that multicollinearity does not occur. Heteroscedasticity Test Table 5. Heteroscedasticity Test Results -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1 - 19 1 - 22 2 - 20 2 - 23 3 - 21 4 - 19 4 - 22 5 - 20 5 - 23 6 - 21 7 - 19 7 - 22 8 - 20 8 - 23 9 - 21 10 - 19 10 - 22 Y Residuals Source: Eviews Data Processing Results 12 Residual graph (blue color) in Table 5. It can be seen that it does not pass the numbers of 500 and -500 which means that the residual variation is the same, therefore it is declared to have passed the heteroscedasticity test (Seventy et al., 2021: 143 in Gunawan et al., 2023). Analysis of the Influence of Average School Length, Per Capita Expenditure, and Life Expectancy on the Human Development Index in West Nusa Tenggara Province in 2019-2023 JEFMS, Volume 08 Issue 10 October 2025 www.ijefm.co.in Page 6951 B. Statistical Test Partial Test (t-test) Table 6. Partial Test (t-test) Dependent Variable: Y Method: Panel Least Squares Date: 09/21/25 Time: 08:39 Sample: 2019 2023 Periods included: 5 Cross-sections included: 10 Total panel (balanced) observations: 50 Variable Coefficient Std. Error t-Statistic Prob. C 27.98865 4.355259 6.426403 0.0000 X1 5.361404 0.882468 6.075464 0.0000 X2 -0.001350 0.000638 -2.115541 0.0412 X3 0.219693 0.110089 1.995596 0.0534 Source: Eviews Data Processing Results 12 Table 6. shows the value of the t-calculation and its probability value of each independent variable. In this study, we used the interpretation of a one-way hypothesis test with a significance value of 0.05 with a t-table value of 2.012896 and a value of df 46 (DF=n-k). Therefore, the hypothesis can be proven in the explanation below. 1. Average School Length (x1) The probability value of the Average School Length (X1) is 0.0000 < 0.05 and the t-calculated value of the t-table > is 6.075464 > 2.012896, which means that the variable of average school time partially has a positive and significant influence on the Human Development Index (Y) variable. 2. Per Capita Expenditure (x2) The probability value of Per Capita Expenditure (X2) is 0.0412 < 0.05 and the t-calculated value of < t-table is -2.115541 < 2.012896, meaning that the per capita expenditure variable partially has a negative and significant influence on the Human Development Index (Y) variable. 3. Life expectancy (x3) The probability value of Life Expectancy (X3) is 0.0534 > 0.05 and the t-calculated value of < t-table is 1.995596 < 2.012896, meaning that the variable life expectancy partially has a positive but not significant effect on the variable of the Human Development Index (Y). Simultaneous Test (F-Test) Table 7. Simultaneous Test (F-Test) Effects Specification Cross-section fixed (dummy variables) Root MSE 0.601728 R-squared 0.980201 Mean dependent var 71.38040 Adjusted R-squared 0.973780 S.D. dependent var 4.319872 S.E. of regression 0.699495 Akaike info criterion 2.341979 Sum squared resid 18.10385 Schwarz criterion 2.839105 Log likelihood -45.54947 Hannan-Quinn crister. 2.531287 F-statistic 152.6521 Durbin-Watson stat 1.922512 Prob(F-statistic) 0.000000 Source: Eviews Data Processing Results 12 Analysis of the Influence of Average School Length, Per Capita Expenditure, and Life Expectancy on the Human Development Index in West Nusa Tenggara Province in 2019-2023 JEFMS, Volume 08 Issue 10 October 2025 www.ijefm.co.in Page 6952 This study is based on the F-statistical value of the results of the Fixed Effect Model regression data processing and the F-table value of 2.806845 where the significance value is 0.05 with a df1 of 3 and the value of df2 of 46, therefore, based on the results of data processing in Table 7. the value of Prob(F-Statistic) is 0.0000 < 0.05 or based on the results of F-calculation > F-table which is 152.6521 > 2.806845, therefore, the variables Average School Length (X1), Expenditure Per Capita (X2), and Life Expectancy (X3) simultaneously and significantly affect the Human Development Index (Y). Coefficient of Determination Test (R2) Table 8. Coefficient of Determination Test (R2) Effects Specification Cross-section fixed (dummy variables) Root MSE 0.601728 R-squared 0.980201 Mean dependent var 71.38040 Adjusted R-squared 0.973780 S.D. dependent var 4.319872 S.E. of regression 0.699495 Akaike info criterion 2.341979 Sum squared resid 18.10385 Schwarz criterion 2.839105 Log likelihood -45.54947 Hannan-Quinn crister. 2.531287 F-statistic 152.6521 Durbin-Watson stat 1.922512 Prob(F-statistic) 0.000000 Source: Eviews Data Processing Results 12 Based on the test results of Table 8. the value of the determinant coefficient or R2 which is based on the results of the Fixed Effect Model regression with the Adjusted R-squared value is 0.973780 which means the variables of Average School Length (X1), Expenditure Per Capita (X2), and Life Expectancy (X3) can affect the variable of the Human Development Index (Y) of 0.973780 or by 97.37 percent. Where 2.63 percent of other variables outside the variables studied to affect the Human Development Index, such as school age expectations, literacy, infrastructure, poverty, and government spending. C. Discussion Average School Length (x1) The increase in the Average School Length has a positive and significant impact on the Human Development Index in West Nusa Tenggara Province from 2019 to 2023. These findings are in line with the results of research conducted by (Hasibuan et al., 2023), the results of the analysis show that there is a partial positive influence between education variables on the Human Development Index in North Sumatra Province. Despite the pandemic COVID-19 The learning process has many obstacles, but the government is trying to balance education in West Nusa Tenggara Province through distance learning policies and free internet quota assistance so that the Average School Length remains stable and does not experience a significant decrease. Assistance in the form of internet quota is considered crucial during the pandemic Covid-19, all students and students continue to undergo learning from home. The West Nusa Tenggara Provincial Education and Culture Office allows the allocation of School Operational Assistance Funds for the procurement of internet quotas for teachers and students during the pandemic Covid-19 (Inside Lombok, 2020). Therefore, the increase in the Average School Length between 2019 and 2023 has a real role in improving the quality of life of the community and accelerating the growth of the Human Development Index in West Nusa Tenggara Province. Per Capita Expenditure (x2) The per capita expenditure of West Nusa Tenggara Province in the period from 2019 to 2023 has a negative and significant influence on the Human Development Index. This is in line with research conducted by Arin Ramadhiani Soleha & Moh. Faizin (2023), where the findings are that the Per Capita Expenditure variable has a negative and significant effect on the Human Development Index of districts/cities of East Java Province for the period of 2017 to 2021. One of the factors is the pandemic COVID-19 Many people do not have jobs and even though there is an increase in expenditure made by the community only for temporary consumptive needs, so that it does not directly contribute to improving the quality of human resources. The informal sector, which is a large part of the economy, has a serious impact, although post-pandemic per capita expenditure has increased, but the quality of life of the community is not necessarily realized. This is what causes per capita expenditure to experience a negative but significant influence on the Human Development Index in West Nusa Tenggara Province, because the increase in needs is spent more on basic needs rather than long-term investment in the education and health sectors.