TY - JOUR
T1 - Optimization of completion schedule forecasting in case study of double-double track development project (Package A) using the probabilistic pert method
AU - Riantini, Leni Sagita
AU - Ichsan, Mohammad
AU - Trigunarsyah, Bambang
AU - Rarasati, Ayomi Dita
AU - Handika, Nuraziz
AU - Lolo, Chrys Adrian
N1 - Publisher Copyright:
© 2024 by author(s).
PY - 2024
Y1 - 2024
N2 - This study aims to identify the risk factors causing the delay in the completion schedule and to determine an optimization strategy for more accurate completion schedule prediction. A validated questionnaire has been used to calculate a risk rating using the analytical hierarchy process (AHP) method, and a Monte Carlo simulation on @RISK 8.2 software was employed to obtain a more accurate prediction of project completion schedules. The study revealed that the dominant risk factors causing project delays are coordination with stakeholders and changes in the scope of work/design review. In addition, the project completion date was determined with a confidence level of 95%. All data used in this study were obtained directly from the case study of the Double-Double Track Development Project (Package A). The key result of this study is the optimization of a risk-based schedule forecast with a 95% confidence level, applicable directly to the scheduling of the Double-Double Track Development Project (Package A). This paper demonstrates the application of Monte Carlo Simulation using @RISK 8.2 software as a project management tool for predicting risk-based-project completion schedules.
AB - This study aims to identify the risk factors causing the delay in the completion schedule and to determine an optimization strategy for more accurate completion schedule prediction. A validated questionnaire has been used to calculate a risk rating using the analytical hierarchy process (AHP) method, and a Monte Carlo simulation on @RISK 8.2 software was employed to obtain a more accurate prediction of project completion schedules. The study revealed that the dominant risk factors causing project delays are coordination with stakeholders and changes in the scope of work/design review. In addition, the project completion date was determined with a confidence level of 95%. All data used in this study were obtained directly from the case study of the Double-Double Track Development Project (Package A). The key result of this study is the optimization of a risk-based schedule forecast with a 95% confidence level, applicable directly to the scheduling of the Double-Double Track Development Project (Package A). This paper demonstrates the application of Monte Carlo Simulation using @RISK 8.2 software as a project management tool for predicting risk-based-project completion schedules.
KW - Monte Carlo simulation
KW - quantitative risk
KW - railway infrastructure
KW - scheduling
UR - http://www.scopus.com/inward/record.url?scp=85204369478&partnerID=8YFLogxK
U2 - 10.24294/jipd.v8i9.7798
DO - 10.24294/jipd.v8i9.7798
M3 - Article
AN - SCOPUS:85204369478
SN - 2572-7923
VL - 8
JO - Journal of Infrastructure, Policy and Development
JF - Journal of Infrastructure, Policy and Development
IS - 9
M1 - 7798
ER -