<![CDATA[Construction project scheduling commonly applies a deterministic approach using the Critical Path Method (CPM) to determine critical activities and project duration. However, this approach often fails to represent the uncertainty of activity durations that frequently occur during project implementation. Such uncertainty may cause deviations from the planned schedule and increase the risk of project delays. Therefore, a probabilistic approach is required to analyze project duration variability more realistically. This study aims to analyze the probability of construction project completion time by integrating the Critical Path Method and Monte Carlo simulation. The case study was conducted on the construction project of the MAN 4 Kampar classroom building with a planned duration of 244 days. The analysis began with developing a project network and identifying the critical path using CPM. The variability of activity durations on the critical path was then modeled using a triangular probability distribution and analyzed through Monte Carlo simulation using Oracle Crystal Ball with 1000 iterations. The simulation results indicate that the project duration follows a probabilistic distribution ranging from 199.13 days to 214.99 days. The project duration at the P50 probability level is 207.58 days, while the P80 and P90 levels are 209.76 days and 210.76 days, respectively. These findings demonstrate that the probabilistic approach provides a more comprehensive representation of project duration variability compared with the deterministic approach. Therefore, the integration of CPM and Monte Carlo simulation is recommended as a probabilistic analysis method in the planning and control of construction project schedules to anticipate project duration uncertainty.]]>
