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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 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 research aims to examine how the predicted years in school and the unemployment rate influence labor force participation (TPAK) in Aceh Province. Across several cities and communities in Aceh, it employs secondary panel data from the Central Bureau of Statistics (BPS).  Panel regression analysis is done using the Random Effect Model (REM) approach in this study. The results show that TPAK is negatively and substantially affected by the unemployment rate, while the projected years of schooling have no significant statistical impact. TPAK changes are generally only marginally affected by either of these causes. The coefficient of determination reveals that the model explains only 8. 3% of the TPAK swings. Although education and unemployment are components of labor market behavior, other, more important variables are more crucial in influencing labor force participation in Aceh, as these results suggest.

This study analyzes the human development index, regional minimum wage, and labor force participation rate on poverty in North Sumatra in 2001-2023. The data used is secondary data in the form of time series obtained from the publication of the Central Bureau of Statistics. The analysis method used is multiple regression with E-Views software. The results showed that the human development index has no effect, the regional minimum wage has a negative effect and the labor force participation rate has a negative and significant effect on poverty, which indicates that an increase in the human development index tends to not affect poverty because it has a positive value. In contrast, the regional minimum wage and labor force participation rate show a negative and significant effect on poverty. Simultaneously, the human development index, regional minimum wage and labor force participation rate have a significant effect on poverty.

This research aims to determine the effect of the human development index and economic growth on unemployment and poverty in Aceh. This research uses secondary data with a time series of 2013-2022 with the scope of Jogjakarta province. This research model uses a path analysis model using the Eviews application. The results of this research show that the number of labor force directly has a positive and insignificant effect on the level of poverty. The human development index directly has a negative and significant effect on the poverty level The number of labor force directly has a negative and significant effect on the unemployment rate. The human development index directly has a positive and significant effect on unemployment. The poverty level directly has a positive and insignificant effect on the unemployment rate. Indirectly, the number of labor force has a negative and insignificant effect on unemployment through poverty. Indirectly, the human development index has a negative and insignificant effect on unemployment through poverty.

This research aims to determine the effect of TPAK and inflation on economic growth in Jambi Province in 2013 - 2022. The object of this research is TPAK and inflation as well as economic growth in Jambi Province. The analytical method used in the research is descriptive quantitative and the analytical tools used in this research are hypothesis testing (f test, t test), multiple linear analysis, R square coefficient of determination test, all data is processed using SPSS. The results of this research reveal the R-square value or coefficient of determination 0.247, which means that the influence of TPAK and inflation in Jambi Province can have an ability of 24.7% in explaining economic growth in Jambi Province, while (100% - 24.7% = 75.3%) is influenced by other factors outside the research variables. The significant test carried out on the TPAK (X1) table is seen from the t-count and t-table values. From the results of the regression carried out, it was obtained that the t-count value was -0.205 and the t-table value was 2.365, so the t-count value < t-table ( -0.205 < 2.365) with a probability sig value of 0.843 > 0.05. So Ho is accepted and Ha is rejected. This means that TPAK has no influence and is not significant on economic growth in Jambi Province. The significant test carried out on the Inflation variable (X2) can be seen from the t-count and t-table values. From the results of the regression carried out, it was obtained that the t-count value was 927 and the t-table value was 2.365, so the t-count value < t-table (927 < 2.365) with a probability value of Sig 0.385 > 0.05. So Ho is accepted and Ha is rejected. This means that inflation has no influence and is not significant on economic growth (Y) in Jambi Province.

This research aims to analyze the influence of the labor force, inflation, unemployment and poverty on economic growth in Indonesia for the period (2014-2022). The variables used are Inflation as the dependent variable, Money Supply (JUB) and Interest Rates as the independent variables. The data used in this research is secondary data obtained from publications by the Indonesian Central Bureau of Statistics. The analytical method used is a multiple linear regression model or Ordinary Least Square (OLS). In processing the data, the author used the help of Eviews 10 software. Based on the estimation results, it was found that there is a relationship between Labor Force, Inflation, Unemployment and Poverty on economic growth in Indonesia and the variables Labor Force, Inflation, Unemployment and Poverty have a positive and significant effect on Economic Growth in Indonesia .      

Economic growth is essentially the most important aspect in a country. An increase in the quality of life of the community that occurs in an area can mean that the area has continued economic growth. Economic growth can be reflected in changes in GRDP in a region. This research uses eviews analysis 10. Labor Force Participation Rate (TPAK), human development index and poverty are among the Human Resource factors that contribute to the formation of Gross Regional Domestic Product (GRDP) which can encourage Economic growth of a region. The aim of this research is to find out the influence of the level of labor force participation and poverty as seen from the human development index on economic growth in the province of West Papua in 2014-2022. The data used in this research uses time series data for the period 2014-2022, using quantitative descriptive methods with the eviews 10 analysis tool. Independent variables consist of Labor Force Participation Rate (TPAK) as X1, human development index (HDI) as X2 and poverty (k) as X3 and Economic Growth as (Y). The results of this study show that TPAK, HDI and K simultaneously have a positive and insignificant effect.

Improper population management will cause population problems, especially in work areas. Existing jobs have not been able to meet the employment needs resulting from the unemployment problem. The number of unemployed in Indonesia reaches 7 million people from the workforce. The aim of this research is to determine the effect of economic growth, minimum wage labor and inflation on unemployment in Indonesia. The analysis technique used is multiple linear regression, using time sequential data for 2014-2023. The test results show that with a 95 percent confidence level the model is significant, indicated by a significance value of F 0.000 < 0.02. Determination coefficient of The R Square for the model obtained a figure of 0.235 which indicates the independent variable. The model is able to explain 95 percent of the variation in endogenous variables well. Meanwhile, the remaining 5 percent is explained by other variables outside these variables model. This means that together the variables are inflation, economic growth and minimum wage workers influence the level of open unemployment. Partially, of the three variables tested by considering the P-value results, there are two Variables that influence the open unemployment rate are inflation and minimum wages worker. Meanwhile, the economic growth variable has no effect on the level of openness unemployment.

At the national and regional levels, sustainable strategies are needed to address complex and ongoing issues, including poverty, unemployment, and regional minimum wages. There are two factors that are the focus of this study: Provincial Minimum Wage in Central Kalimantan Province: 1) The Impact of Education Level on Poverty and Unemployment; and 2) The Impact of Early Labor Force Participation Rate on Poverty and Unemployment through the Regional Minimum Wage. Time series data from 2014 to 2023 is used as secondary data in this study. The type of data used is quantitative data. The data was analyzed using path analysis, and SPPS 25 was the analysis tool used. Based on the findings, there is a significant indirect relationship between unemployment and poverty and education level. In addition, there is a significant indirect relationship between unemployment and poverty with the initial labor force participation rate, which is influenced by the regional minimum wage.

Economic growth underscores the important role of the state in enhancing human resource development. An important part of production factors is human resources, especially in terms of quality. Labor productivity is increased through improving the quality of human capital through education and health. This study is to examine the effect of human capital and the level of labor force participation on Indonesia's economic growth. This study uses the panel data method from 34 provinces in Indonesia for the 2015-2019 period. The results of statistical tests show that the education variable has a positive effect on the dependent variable of economic growth, while the health variable and the labor force participation rate variable have no effect on economic growth

Peramalan merupakan proses untuk memperkirakan beberapa kebutuhan di masa yang akan datang, yang meliputi kebutuhan dalam ukuran kuantitas, kualitas, waktu dan lokasi yang dibutuhkan dalam rangka memenuhi permintaan barang atau pun jasa. Penelitian ini bertujuan untuk meramalkan jumlah angkatan kerja di Kota Medan menggunakan metode Trend Non Linear Kubik. Data yang diperlukan untuk penelitian ini adalah data jumlah angkatan kerja di Kota Medan dari tahun 2011-2020 dan Sumber data penelitian ini diperoleh dari Badan Pusat Statistik (BPS) Kota Medan. Data tersebut dianalisis dengan metode Trend Non Linear Kubik  untuk meramalkan jumlah angkatan kerja pada tahun 2021 dan pengolahan datanya menggunakan software SPSS. Hasil analisis Model peramalan jumlah angkatan kerja di Kota Medan menggunakan metode Trend Non Linear Kubik diperoleh persamaan modelnya adalah y=512819+155612x-28928x^2+1754x^3 dan hasil keakurasian model sebesar 3,94%, peramalan yang dilakukan menghasilkan jumlah angkatan kerja di Kota Medan untuk tahun 2021 adalah 1.058.837.

Jika ada lebih banyak investor asing di suatu negara daripada jumlah pekerja, ekonomi tumbuh lebih cepat. Studi kuantitatif ini menggunakan data investasi enam tahun sebelumnya di Indonesia dan pertumbuhan lapangan kerja. Data sekunder digunakan. Website Badan Koordinasi Penanaman Modal (BKPM) dan Badan Pusat Statistik adalah contoh sumber data sekunder. Dengan program Eviews 8, regresi linier sederhana digunakan sebagai alat analisis. Hasil penelitian menunjukkan bahwa perluasan tenaga kerja dipengaruhi secara signifikan oleh semua variabel independen. Dengan koefisien determinasi (R square) sebesar 0,815076, maka faktor variabel penanaman modal asing sebesar 81,5 persen dapat menjelaskan pertumbuhan tenaga kerja. Sisanya sebesar 18,5% dari pertumbuhan angkatan kerja Indonesia dapat dijelaskan oleh variabel lain yang tidak dimasukkan dalam model analisis penelitian ini.

Penelitian ini memiliki tujuan untuk mengetahui pengaruh dari Penanaman Modal Asing (PMA), Penanaman Modal Dalam Negeri (PMDN) dan Angkatan Kerja terhadap Pertumbuhan Ekonomi di Provinsi Banten. Penelitian ini dilakukan pada periode tahun 2017 sampai 2020. PDRB diartikan sebagai jumlah seluruh nilai total barang dan jasa akhir yang dihasilkan oleh semua unit ekonomi di wilayah tertentu atau bisa juga diartikan sebagai nilai tambah total yang dihasilkan oleh semua unit usaha dalam suatu wilayah. Penanaman Modal Asing (PMA) berpengaruh positif namun tidak signifikan terhadap pertumbuhan ekonomi di Provinsi Banten dengan nilai koefisien sebesar 0.001388. Penanaman Modal Dalam Negeri (PMDN) berpengaruh positif dan signifikan terhadap pertumbuhan ekonomi di Provinsi Banten dengan nilai koefisien sebesar 0.005665. Angkatan Kerja (AK) berpengaruh positif namun tidak signifikan terhadap pertumbuhan ekonomi di Provinsi Banten dengan nilai koefisien sebesar 0.006446. Variabel penelitian Penanaman Modal Asing (PMA), Penanaman Modal Dalam Negeri (PMDN) dan Angkatan Kerja secara bersama-sama berpengaruh dan signifikan terhadap pertumbuhan ekonomi di Provinsi Banten.