Implementation of Earned Value Management (EVM) method in analyzing delays in construction projects using python programming

Construction projects are inherently complex and dynamic, involving the management of Construction projects frequently face delays that lead to budget overruns and reduced stakeholder satisfaction. Earned Value Management (EVM) offers a quantitative approach for assessing time and cost performance by integrating planned value, earned value, and actual cost, allowing project managers to calculate objective indicators such as the Cost Performance Index (CPI) and Schedule Performance Index (SPI). However, manual EVM calculations in large-scale projects are often inefficient and prone to error. This study aims to implement the EVM method using Python programming to analyze delays in the Santa Ursula Female Dormitory Building construction project. The system developed automates the calculation of EVM indicators while providing visualization and report generation for effective project monitoring. Results indicate that the project experiences a delay of 12.5 weeks from the planned 80 weeks, with an estimated completion duration of 92.5 weeks. Additionally, the estimated cost at completion is IDR 21,115,552,959, which exceeds the planned budget of IDR 18,712,612,545, reflecting significant cost overruns. The application of Python programming in EVM analysis enhances the speed, accuracy, and systematic assessment of project performance, enabling real-time monitoring and data-driven decision-making for project managers. This study demonstrates that integrating EVM with Python programming can effectively address delays and budget deviations, improving project management practices in the construction sector.