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Based on data from the Central Statistics Agency (BPS) from 2021 to 2023, the crime rate in Indonesia increased by 345,510 cases. This increase indicates social problems, particularly in the economic sector. Factors such as high unemployment, high poverty rates, and low minimum wages are the main causes driving crime. When people's basic needs are not met, the potential for deviant behavior to meet their living needs tends to increase. This study aims to analyze the influence of unemployment, poverty, and the Provincial Minimum Wage (UMP) on crime rates in Indonesia, both partially and simultaneously. The study uses a quantitative approach with secondary data sources obtained from official BPS publications. The data used is panel data, namely a combination of time series (time span) and cross-section (across regions/provinces) data for the period 2021–2023. Data analysis was performed using a panel data regression model with a Fixed Effect Model (FEM) approach after undergoing the Hausman Test. The results show that partially, the three variables—unemployment, poverty, and the UMP—have a significant influence on crime rates. Simultaneous testing also showed that collectively, these three variables significantly influence the crime rate. Furthermore, the coefficient of determination (R²) test result of 93.5% indicates that unemployment, poverty, and the minimum wage (UMP) variables are able to explain most of the variation in crime rates in Indonesia during the study period, while the remaining 6.5% is influenced by other variables not included in the model. This finding emphasizes the importance of improving the economic conditions of the community through job creation, poverty alleviation, and minimum wage adjustments as preventative measures to reduce crime rates in Indonesia.

This study aims to analyze the influence of the Provincial Minimum Wage (UMP), Poverty Rate (TK), and Unemployment Rate (TPT) on the Human Development Index (HDI) in five provinces of Indonesia categorized as having moderate HDI from 2014 to 2023. The research employs a panel data regression method using the Fixed Effect Model (FEM) approach to capture variations across regions and time.The findings reveal that the UMP has a positive and significant impact on HDI, indicating that higher minimum wages contribute to improvements in human development. In contrast, the TPT negatively and significantly affects HDI, suggesting that higher unemployment rates hinder human development progress. Meanwhile, the TK variable shows no significant effect on HDI, implying that changes in poverty rates during the study period did not directly influence human development levels in these provinces.Furthermore, the results of the regression analysis show that UMP, TK, and TPT simultaneously have a significant impact on HDI, with an overall contribution of 98.65%. The remaining 1.35% is attributed to other factors not included in the research model.These results highlight the importance of policies aimed at increasing minimum wages and reducing unemployment to enhance community welfare and accelerate human development in provinces with moderate HDI. Policymakers are encouraged to design comprehensive strategies that prioritize employment creation and wage improvements as key levers for boosting human development outcomes across regions.

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.