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This research is motivated by the problem of the open unemployment rate in Maluku Province which is still fluctuating, where the influence of human capital indicators such as the Average Years of Schooling and the Gross Enrollment Rate of Senior High Schools as well as economic policies such as the Provincial Minimum Wage often show results inconsistent with theory, thus requiring further empirical studies to determine their influence in the region. The purpose of this study is to analyze and determine the partial and simultaneous effects of the average years of schooling, the gross enrollment rate of senior high schools, and the provincial minimum wage on the open unemployment rate in Maluku Province. The method used is quantitative with secondary data in the form of time series from 2015 to 2024 sourced from the Central Statistics Agency (BPS) of Maluku Province, and analyzed using multiple linear regression techniques. The results show that the average years of schooling have a negative and significant effect, while the gross enrollment rate of senior high schools and the provincial minimum wage each have a positive insignificant and negative insignificant effect on the open unemployment rate. Simultaneously, the three variables also have no significant effect. The implications of these findings confirm that increasing the average length of schooling is a key factor in reducing unemployment, but policies related to minimum wages and high school participation need to be reviewed and combined with other policies to be more effective in addressing unemployment in Maluku Province.  

Unemployment is a socio-economic problem that can threaten the stability of the Indonesian economy. This study analyzes the effect of minimum wages, exports, foreign investment, and the human development index (HDI) on the unemployment raefrom 1990 to 2023. Using the Ordinary Least Square (OLS) multiple linear regression estimation method, to correct bias in the estimation, the Newey-West HAC standard errors approach is used. Minimum wages and foreign investment have a significant negative effect on the open unemployment rate, confirming that wage increases can boost productivity, foreign investment creates direct jobs through the construction of production facilities and economic multiplier effects in supporting sectors. The most surprising finding of the HDI which has a positive effect and exports which are proven to be insignificant on the unemployment rate, this shows that human capital formation is not in line with existing job opportunities due to rapid technological changes, as well as export-increasing policies which focus more on capital intensity. The study provides important implications for policymakers, maintaining and optimizing minimum wage increases and foreign investment in a measurable manner because they have proven effective in reducing unemployment rates. Reorienting export strategies policy from capital-intensive to labor-intensive, increasing the human development index adjusted to technological developments, especially in the business and industrial world.

This study aims to apply the Principal Component Analysis (PCA) method to identify the main factors influencing poverty in North Sumatra Province. Poverty rates in this region show significant variations among districts and cities, influenced by differences in social, economic, educational, and basic facility availability. The data used in this study include eleven indicators related to population, education, health, access to basic services, and economic conditions. All variables were initially normalized to ensure they had comparable scales, then PCA feasibility tests were conducted using MSA, KMO, and Bartlett's test, which indicated that the data were eligible for further analysis. The results of the PCA revealed three main components explaining a total of 69.91 percent of the variation. The first component represents regional population and economic factors, with the largest contributions coming from population density, open unemployment rate, and per capita expenditure. The second component reflects household living conditions, such as access to clean water, adequate sanitation, and health complaints. The third component describes the educational dimension through indicators of the population aged at the primary and secondary school levels. These findings indicate that poverty in North Sumatra is influenced not only by economic factors but also by the quality of basic services and education levels among the population. Therefore, this research is useful for policymakers at the central and regional government levels to consider the factors influencing the increase in poverty in North Sumatra.

This study aims to analyze the factors affecting real wages of construction workers across provinces in Indonesia from 2010 to 2023 using panel data analysis. The independent variables include Provincial Minimum Wage (UMP), Consumer Price Index (CPI), Open Unemployment Rate (TPT), and Performance Pay (Balas Jasa). A panel dataset of 476 observations from 34 provinces over 14 years was analyzed using three model approaches: Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM). The best model was determined through Chow Test, Hausman Test, and Lagrange Multiplier Test, which confirmed that the Fixed Effect Model (FEM) is the most appropriate for analyzing this research data. FEM estimation results show that simultneously, all independent variables (UMP, CPI, TPT, and Performance Pay) have a significant effect on real wages with an F-statistic value of 436,465.9 (p-value = 0.0000 < 0.05), indicating that the model as a whole is highly valid and capable of explaining the variation in real wages collectively. However, partial tests reveal that only the Real Wage variable has a positive and statistically significant effect on Performance Pay (coefficient = 106.3320; t-statistic = 1276.083; p-value = 0.0000), while UMP (p-value = 0.1472), CPI (p-value = 0.6460), and TPT (p-value = 0.6934) show no significant effects at the 5% significance level. The research model demonstrates very high predictive ability with an R-squared value of 0.999735 (99.97%), indicating that the variables studied can explain nearly all variation in real wages of construction workers at the provincial level. This research provides policy implications that improving real wages in the construction sector requires an integrated approach that focuses not only on minimum wage setting but also on regional inflation control, human capital quality improvement, and creating conducive labor market conditions through unemployment reduction

The purpose of this study is to investigate the factors that lead to poverty in different Indonesian regions between 2018 up to 2024. The Gross Regional Domestic Product per capita, the Human Development Index, and the Open Unemployment Rate are the independent factors used in this study, whereas poverty levels are the dependent variable. The Central Statistics Agency provided secondary data that was used in a quantitative manner. Using EViews 12 software, panel regression techniques were used to process the data. The study's conclusions show that, at a significance level of less than 0.05, economic and human development factors simultaneously significantly affect poverty rates across Indonesian regions. The coefficient of determination indicates that the variables in the model can account for the majority of the variations in poverty levels. These findings demonstrate how important a region's economic status and level of human development are to efforts to reduce poverty. It is anticipated that this research will help the government develop more effective and long-lasting methods for reducing poverty.

This study aims to analyze the effect of the unemployment rate on economic growth in Riau Islands Province in 2024 using a descriptive–quantitative approach based on official data published by Statistics Indonesia (BPS). The analysis was conducted through year-on-year and quarter-to-quarter measurements of Gross Regional Domestic Product (GRDP), as well as the dynamics of the Open Unemployment Rate (OUR) throughout the year. The findings show that the average economic growth of the province in 2024 reached 5.02 percent, while the unemployment rate decreased from 6.94 percent in February to 6.39 percent in August. Pearson correlation analysis resulted in r = –0.98 (p < 0.05), indicating a very strong negative relationship between unemployment and GRDP growth. Meanwhile, the simple linear regression model produced the equation Ŷ = 5.45 – 0.22X with an R² of 0.96, implying that 96 percent of the variation in economic growth can be explained by changes in the unemployment rate. These findings are consistent with Okun’s Law, suggesting that increased industrial and trade activities in the province contribute to reducing unemployment. The study concludes that strengthening sectoral job creation, improving labor productivity, and enhancing labor market monitoring are crucial to support inclusive and sustainable economic growth in the Riau Islands Province.

This study aims to determine the partial and simultaneous influence between the variables of labor force, the agricultural sector, economic growth, and the industrial sector on the open unemployment rate in Aceh Province in the 2014–2023 period. The research method uses a quantitative approach by utilizing secondary data obtained from related agencies. The results showed that the labor force variable (X1) had a significant influence on the open unemployment rate with a significance value of 0.000 < 0.05. The agricultural sector variable (X2) was also proven to have a significant effect with a significance value of 0.002 < 0.05. Furthermore, economic growth (X3) has a significant influence on open unemployment with a significance value of 0.004 < 0.05. The industrial sector variable (X4) also showed a significant influence on the open unemployment rate in Aceh Province with a significance value of 0.015 < 0.05. Overall, these results indicate that employment dynamics and regional economic structure play an important role in determining the open unemployment rate during the study period. These findings provide a basis for policymakers to formulate more effective economic development strategies in reducing unemployment in the future.

Poverty is one of the most difficult economic problems to solve. This problem occurs in all countries. Among the causes of poverty are poor human resources, a low quality of life, a rising unemployment rate, and a decrease in job availability each year, as well as wages that do not match living costs. This is not only due to low human resources; the government also plays a crucial role in this issue. The poverty rate is unavoidable, so an appropriate solution is needed to address this issue. One step to reducing poverty is to analyze which economic instruments can be optimized, especially in the Sidoarjo region. The poverty rate in Sidoarjo is quite high. The open unemployment rate in Sidoarjo ranks third in East Java province. Therefore, the author was interested in conducting this research. This study aims to determine the effect of the distribution of zakat, infaq, and alms (ZIS) funds, GRDP, and open unemployment on the poverty rate in Sidoarjo in 2013-2023. This study uses a quantitative method with multiple linear regression analysis. The data processing tool used is SPSS. The results of the T test indicate that the distribution of ZIS funds has a significant effect on the poverty rate, while GRDP and open unemployment do not have a significant effect on the poverty rate partially. The F test shows that the distribution of ZIS funds, inflation, and GDP have a significant effect on the poverty rate simultaneously in the period 2013-2023. The limitation of this study is the use of variables that affect the poverty rate, so that future researchers can add or change these variables with other variables related to poverty.

Macroeconomic indicators are essential instruments in the process of planning a country's development. Assumptions regarding inflation, unemployment, and economic growth are often used by governments to determine macroeconomic policies. Given this context, it becomes important to empirically understand the relationship among these three macroeconomic indicators in Indonesia. This study statistically examines the relationship between the variables of inflation, unemployment, and economic growth using the Vector Error Correction Model (VECM) method. The results show that inflation and the open unemployment rate significantly influence economic growth. Inflation has a positive relationship with economic growth, while the open unemployment rate has an inverse relationship with economic growth. In the short term, economic growth is significantly affected by the growth rate in the previous period (lag-1 or t-1). Meanwhile, inflation and the open unemployment rate do not statistically have a significant impact on economic growth. Shocks to inflation and the open unemployment rate are relatively not excessively responded to by economic growth.

The Human Development Index (HDI) functions as a key indicator for assessing the level of welfare and overall quality of life of the population within a specific region. This study aims to examine the socio-economic factors influencing HDI at the provincial level in Indonesia using a Gaussian kernel regression approach. A nonparametric method is employed due to its flexibility in capturing nonlinear relationships between the response and predictor variables without the need to assume a specific functional form. The analysis utilizes secondary data, including education, poverty, per capita expenditure, expected years of schooling, open unemployment rate, and gross regional domestic product for each Indonesian province. The findings from this study indicate that educational factors, particularly mean years of schooling and expected years of schooling, exert the most significant impact on HDI improvement. The estimated Gaussian kernel regression model demonstrates a coefficient of determination of 0.9954 and a residual standard error of 0.3468, reflecting a very high predictive accuracy and relatively low error. These results suggest that Gaussian kernel regression is an effective nonparametric approach for analyzing human development in Indonesia.

This study investigates the influence of economic growth, investment, and minimum wage on the open unemployment rate across districts and cities in East Kalimantan Province. The research employs a quantitative descriptive approach with panel data regression analysis, processed using EViews 13 software. Model selection was carried out through the Chow and Hausman tests, which identified the Fixed Effect Model (FEM) as the most appropriate estimation technique. The study utilizes secondary data from 2018 to 2024, obtained from the Central Bureau of Statistics (BPS) and the Investment and One-Stop Integrated Service Office of East Kalimantan Province. The empirical findings demonstrate that economic growth exerts a negative and statistically significant impact on the open unemployment rate, indicating that higher economic growth effectively contributes to reducing unemployment in the region. Foreign Investment (PMA) is found to have a negative but insignificant effect, suggesting that inflows of foreign capital alone do not directly translate into job creation unless accompanied by supporting policies and local labor absorption capacity. In contrast, Domestic Investment (PMDN) shows a positive yet statistically insignificant relationship with unemployment, reflecting the possibility that domestic investments may not always generate sufficient employment opportunities in the short term due to structural constraints or sectoral imbalances. Furthermore, the minimum wage variable has a negative and significant effect on the open unemployment rate, implying that increases in the regional minimum wage can stimulate greater employment absorption and improve labor market conditions. Overall, the results highlight the importance of fostering sustained economic growth and designing investment policies that are more labor-intensive to optimize employment creation. Additionally, the findings emphasize the strategic role of minimum wage policy in supporting job opportunities while safeguarding workers’ welfare.

This study aims to examine the influence of the Gini Ratio, Human Development Index (HDI), and Labor Force Participation Rate (LFPR) on the open unemployment rate in Lampung Province during the 2019–2023 period. The method used in the analysis is a fixed effect model approach with panel data regression, based on secondary data obtained from the Central Statistics Agency (BPS) of Lampung Province. The results of the partial test (t-test) indicate that the three independent variables—the Gini ratio, HDI, and LFPR—do not have a significant effect individually on the open unemployment rate in the region. However, the adjusted coefficient of determination (adjusted R²) value of 88.95% indicates that the model can explain almost all the variation that occurs in the open unemployment rate. This shows that although these variables are statistically insignificant in the model, theoretically they still have an important role in explaining unemployment dynamics in Lampung, along with other factors not yet included in the model. This research provides a strong basis for further analysis in formulating unemployment reduction policies, particularly in regions with economic and social characteristics such as Lampung. Recommendations from this study point to the need for a more comprehensive policy approach that considers other macroeconomic variables such as investment, industrial sector growth, and the quality of education and job training to effectively and sustainably reduce unemployment at the regional level.

This study explores employment development strategies aimed at bolstering economic growth in North Sumatra Province using the Vector Autoregression (VAR) model and an eighteen-year time series dataset. The variables analyzed include the Human Development Index (HDI), total population, Gross Regional Domestic Product (GRDP), Labor Force Participation Rate (LFPR), and Open Unemployment Rate (OUR). The estimation results reveal dynamic interrelationships among these variables over short, medium, and long-term periods. The VAR analysis with a lag of 2 illustrates how each variable contributes to both itself and the other variables. It also shows that past variables (t-1) significantly impact current variables. Furthermore, the response function analysis identifies how a change in one variable is responded to by others across different time horizons. Stability analysis confirms that all variables maintain medium-to-long-term stability over a five-year period. The Forecast Error Variance Decomposition (FEVD) highlights HDI, population, and GRDP as the most influential variables in shaping the employment system and economic development overall. The VAR model used meets the stability test criteria, making the findings a reliable basis for policy research.

This study aims to examine the influence of the number of poor people, average years of schooling, and labor force participation rate on the open unemployment rate (OUR) in Maluku Province from 2017 to 2023. The study uses panel data from 11 districts/cities and applies a regression model using a fixed effect approach. The results show that the average years of schooling have a positive and significant effect on the open unemployment rate. This implies that the longer an individual pursues education, the higher the likelihood of unemployment, as they tend to have higher job expectations and are less willing to accept available jobs. Meanwhile, the labor force participation rate has a negative and significant effect, indicating that a higher number of actively working individuals leads to a lower unemployment rate. The number of poor people does not have a significant effect on unemployment. Overall, the model explains approximately 53.5% of the variation in the open unemployment rate. These findings indicate that education and labor participation are crucial factors in reducing unemployment, but must be supported by the availability of suitable employment opportunities.

This study investigates the impact of household consumption and investment on the open unemployment rate in West Kalimantan over both short and long terms. Using time series data from 1995–2024 and employing the Vector Error Correction Model (VECM) in EViews 12, results show all variables become stationary after first differencing. Johansen cointegration confirms a long-run equilibrium relationship. VECM findings reveal that investment significantly increases unemployment in the long run, while household consumption has no significant effect. In the short term, a significant error correction mechanism exists, indicating adjustment toward long-run equilibrium. Diagnostic tests confirm model validity through absence of autocorrelation and normally distributed residuals. These results highlight the need for more targeted policies to reduce unemployment.

This study aims ti analyze the effect of the Human Development Index (HDI), Gross Regional Domestic Product (GRDP), and Open Unemployment Rate (OUR) on the poverty rate in Gorontalo Province. The study uses panel data from six districts/cities over the period 2017–2024 and is analyzed using panel data regression methods. Based on the results of the Chow test, Hausman test, and Lagrange Multiplier test, the best model used is the Fixed Effect Model (FEM). The analysis results show that simultaneously, the three independent variables have a significant effect on the poverty rate. However, partially, only the GRDP variable has a negative and significant effect on poverty. Meanwhile, the HDI and OUR variables show a negative but statistically insignificant effect on the poverty rate in Gorontalo Province.

This study aims to analyze the effect of population size and open unemployment rate on the Human Development Index (HDI) in Riau Province. The research method used is a descriptive quantitative approach with multiple linear regression analysis. The data used is secondary data based on districts/cities in Riau Province obtained from the Central Statistics Agency (BPS). The analysis results indicate that population size has a positive and significant effect on the HDI, while the open unemployment rate has a negative and significant effect. The F-test also shows that both variables simultaneously have a significant effect on the HDI. The R-squared value of 56.08% indicates that the model adequately explains the variation in the HDI. These findings suggest that improving population quality and reducing unemployment rates are key factors in enhancing human development quality in Riau Province.

Unemployment remains a structural problem in Indonesia with an open unemployment rate reaching 4.91% (BPS, 2024). This study aims to examine the concept of kasb (earning a living) from the perspective of Imam Al-Syaibani and its relevance in the socio-economic context of contemporary Indonesia. The method used is a qualitative literature study with a descriptive-analytical approach, collecting and analyzing classical to contemporary literature related to Al-Syaibani's thoughts and the issue of unemployment. The results of the study show that the concept of kasb emphasizes work as worship that must be carried out in a halal manner, oriented towards a balance between individual (self-interest) and social (public-interest) interests. Al-Syaibani classifies economic endeavors into four types: ijarah (rent), tijarah (trade), zaira'ah (agriculture), and sina'ah (industry), with agriculture as the main sector that brings blessings. This concept is relevant to improving work ethic, productivity, and social responsibility, so that it can be a theoretical and practical solution in reducing unemployment. The integration of spiritual values ​​in economic activities, such as the intention of worship and fair distribution of wealth, can encourage collective welfare. This study contributes to the development of Islamic economics by offering a holistic perspective that combines moral and technical dimensions in overcoming unemployment

One of the goals of development is equity, balance, and justice. This study aims to analyze the regional balance in East Java Province. Using a quantitative approach, this study analyzes development disparities between regions in East Java province. The data used include indicators of regional balance from various districts or cities in East Java and see the relationship between the dependent variable Percentage of Poor Population and the independent variables Regional Minimum Wage (RMW), Human Development Index (HDI), Gross Regional Domestic Product (GRDP), and Open Unemployment Rate (OUR). The analysis method used is the primacy index to measure regional imbalance. The results showed that simultaneously, RMW, HDI, GRDP, and OUR have a significant effect on the percentage of poor people. At the same time, partially, there is a substantial effect of RMW on the percentage of poor people, there is a significant effect of HDI on the percentage of poor people, there is no significant effect of GRDP on the percentage of poor people, and there is no significant effect of OUR on the percentage of poor people.

Poverty is a crucial issue for a country. Overcoming poverty requires a comprehensive and sustainable approach that encompasses various sectors.  This study aims to determine the effect of the Open Unemployment Rate (TPT), Gross Regional Domestic Product (PDRB), and Labor Force Participation Rate (TPAK) on the number of poor residents.  The data analysis technique used in this research is OLS (Ordinary Least Squares), utilizing time series data on the Open Unemployment Rate (TPT), Regional Gross Domestic Product (PDRB), Labor Force Participation Rate (TPAK), and poverty from 2002-2023 in North Sumatra Province.  The results of this study indicate that the Open Unemployment Rate (IPT) does not affect poverty, whereas the Gross Regional Domestic Product (PDRB) and the Labor Force Participation Rate (TPAK) have a negative and significant impact on poverty.  Meanwhile, simultaneously, the Open Unemployment Rate (TPT), Regional Gross Domestic Product (PDRB), and Labor Force Participation Rate (TPAK) affect poverty in North Sumatra Province from 2002 to 2023.