Performance-Based Cost and Time Prediction Analysis of Tertiary Irrigation Projects Using Artificial Neural Network

The LOS-04 project, a tertiary irrigation work package of the Rentang Irrigation Modernization Project (RIMP), has been ongoing for 26 months with a physical progress of 60.95%.This study aims to analyze project performance and predict the final cost and completion time by integrating Earned Value Management (EVM) with Artificial Neural Network (ANN).The EVM analysis revealed a Cost Performance Index (CPI) of 0.975 and a Schedule Performance Index (SPI) of 0.687, indicating that the project is experiencing cost overruns and significant schedule delays.To improve forecasting accuracy, an ANN model was developed using historical project data.The integration of EVM and ANN predicts a final project cost of Rp. 150.2 billion and a total duration of 52 months.These findings provide critical insights for project monitoring and evaluation, allowing stakeholders to formulate necessary corrective actions to mitigate further risks.