Penerapan Regresi Linier Dalam Memprediksi Upah Minimum Provinsi Di Indonesia - Bright Nine Ginting; Khairun Nadiah; Grace Oktavia; Daniel Sembiring (Universitas Maritim AMNI Semarang, 2024)
This research aims to evaluate the effectiveness of linear regression as a forecasting tool to estimate the Provincial Minimum Wage (UMP) in Indonesia. Utilizing UMP data from various provinces during the period 2002-2022, this study employs linear regression to analyze the factors influencing UMP determination. The predicted UMP for North Sumatra in 2023 demonstrates a high level of accuracy (R-squared = 0.9678), affirming the potential of linear regression as an effective tool to understand regional economic dynamics. The research provides a crucial foundation for policymakers in regional economic planning and suggests avenues for further investigation, including exploring alternative prediction methods and analyzing the impact of UMP regulation policies.