This study aims to analyze the effects of domestic investments, inflasi, and pengeluaran on Sumatra Utara's income between 2001 and 2020. This study uses the Error Correction Model (ECM) analysis method to determine the impact of independent variables on dependent variables in the pendek data and the Regression Linear Berganda analysis to determine the impact of independent variables on dependent variables in the panjang data. According to the results of the ECM analysis, the variable pengeluaran in the panjang has a significant and positive impact on the sumatera utara's income, while the variable PMDN in the panjang has a positive but not significant effect, and inflasi has a negative and not significant effect. Conversely, the pendek jangka indicates that the pengeluaran variable also has a significant and positive impact on the Sumatera Utara's income, whereas the PMDN and Inflasi variables do not have a significant impact.

Poverty has become a quite burdensome economic challenge for developing countries. In addition, poverty is also closely linked to inequality. In Indonesia, poverty is one of the economic challenges that is difficult to face to date. This study examines the effect of Investment, TPT and UMR on poverty in West Sumatra in 2010-2024. The data used are secondary time series data obtained through the BPS website. The analysis method used is the multiple regression analysis method using the E-views tool. The results of the study show that Investment has a significant negative effect on poverty, the Open Unemployment Rate has a positive effect, but is not significant on poverty, and UMR has a significant negative effect on poverty. Simultaneously, these three variables have a significant effect on poverty.

One of the socioeconomic problems faced by every region is poverty. Poverty is a social issue that takes place in the long term, so that until now it is still difficult to overcome. The purpose of this study was to determine the effect of Population, Open Unemployment Rate (TPT), and Human Development Index on Poverty Level in North Sumatra Province. This study uses secondary data analysis in the form of time series data which is quantitative in nature, namely data in the form of numbers. The secondary data used in this study are poverty data, population data, open unemployment rate data and human development index data from 2001 to 2021. These data were obtained from the North Sumatra in Figures (SUDA) document from 2001 to 2021. The results of this study prove that population has a significant effect on the poverty rate of North Sumatra Province, the open unemployment rate variable has no significant effect on the poverty rate of North Sumatra Province, the human development index variable has no significant effect on the poverty rate of North Sumatra Province. Simultaneously, population, open unemployment rate (TPT), and human development index have a significant effect on the poverty rate in North Sumatra province.

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 find out how much influence the unemployment rate, human capital and population have on poverty in the 2018-2022 period. This research uses quantitative methods with descriptive analysis. The data used in this research is secondary data sourced from the Central Statistics Agency (BPS) of North Sumatra for 4 years from 2018-2022. The data analysis technique uses Random Effect based on the results of the Lagrange Multiplier test. The results of this research show that (1) the independent variables, namely open unemployment, human capital, and population have a significant effect on poverty in North Sumatra province, (2) the level of open unemployment and population have a positive effect and have a significant influence on poverty in North Sumatra, and (3) the Human Capital variable has a negative effect and has a significant influence on poverty in North Sumatra.