Bayesian-based Project Monitoring: Framework Development and Model Testing
During project implementation, risk becomes an integral part of project monitoring. Therefore. a tool that could dynamically include elements of risk in project progress monitoring is needed. This objective of this study is to develop a general framework that addresses such a concern. The developed...
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Petra Christian University
2015-12-01
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doaj-28b7d8dde69f4b56bd4073f0369dd4a12020-11-24T23:28:38ZengPetra Christian UniversityJurnal Teknik Industri1411-24852087-74392015-12-011726170Bayesian-based Project Monitoring: Framework Development and Model TestingBudi Hartono0Riesa Ayuningtyas1Yun Prihantina Mulyani2 Industrial Engineering Program, <br />Mechanical and Industrial Engineering Department, Universitas Gadjah Mada <br />Jl. Grafika 2, Yogyakarta Industrial Engineering Program, <br />Mechanical and Industrial Engineering Department, Universitas Gadjah Mada <br />Jl. Grafika 2, Yogyakarta Industrial Engineering Program, <br />Mechanical and Industrial Engineering Department, Universitas Gadjah Mada <br />Jl. Grafika 2, Yogyakarta During project implementation, risk becomes an integral part of project monitoring. Therefore. a tool that could dynamically include elements of risk in project progress monitoring is needed. This objective of this study is to develop a general framework that addresses such a concern. The developed framework consists of three interrelated major building blocks, namely: Risk Register (RR), Bayesian Network (BN), and Project Time Networks (PTN) for dynamic project monitoring. RR is used to list and to categorize identified project risks. PTN is utilized for modeling the relationship between project activities. BN is used to reflect the interdependence among risk factors and to bridge RR and PTN. A residential development project is chosen as a working example and the result shows that the proposed framework has been successfully applied. The specific model of the development project is also successfully developed and is used to monitor the project progress. It is shown in this study that the proposed BN-based model provides superior performance in terms of forecast accuracy compared to the extant models.http://puslit2.petra.ac.id/ejournal/index.php/ind/article/view/19319Bayesian NetworksRisk RegisterRisk FactorsProject Monitoring |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Budi Hartono Riesa Ayuningtyas Yun Prihantina Mulyani |
spellingShingle |
Budi Hartono Riesa Ayuningtyas Yun Prihantina Mulyani Bayesian-based Project Monitoring: Framework Development and Model Testing Jurnal Teknik Industri Bayesian Networks Risk Register Risk Factors Project Monitoring |
author_facet |
Budi Hartono Riesa Ayuningtyas Yun Prihantina Mulyani |
author_sort |
Budi Hartono |
title |
Bayesian-based Project Monitoring: Framework Development and Model Testing |
title_short |
Bayesian-based Project Monitoring: Framework Development and Model Testing |
title_full |
Bayesian-based Project Monitoring: Framework Development and Model Testing |
title_fullStr |
Bayesian-based Project Monitoring: Framework Development and Model Testing |
title_full_unstemmed |
Bayesian-based Project Monitoring: Framework Development and Model Testing |
title_sort |
bayesian-based project monitoring: framework development and model testing |
publisher |
Petra Christian University |
series |
Jurnal Teknik Industri |
issn |
1411-2485 2087-7439 |
publishDate |
2015-12-01 |
description |
During project implementation, risk becomes an integral part of project monitoring. Therefore. a tool that could dynamically include elements of risk in project progress monitoring is needed. This objective of this study is to develop a general framework that addresses such a concern. The developed framework consists of three interrelated major building blocks, namely: Risk Register (RR), Bayesian Network (BN), and Project Time Networks (PTN) for dynamic project monitoring. RR is used to list and to categorize identified project risks. PTN is utilized for modeling the relationship between project activities. BN is used to reflect the interdependence among risk factors and to bridge RR and PTN. A residential development project is chosen as a working example and the result shows that the proposed framework has been successfully applied. The specific model of the development project is also successfully developed and is used to monitor the project progress. It is shown in this study that the proposed BN-based model provides superior performance in terms of forecast accuracy compared to the extant models. |
topic |
Bayesian Networks Risk Register Risk Factors Project Monitoring |
url |
http://puslit2.petra.ac.id/ejournal/index.php/ind/article/view/19319 |
work_keys_str_mv |
AT budihartono bayesianbasedprojectmonitoringframeworkdevelopmentandmodeltesting AT riesaayuningtyas bayesianbasedprojectmonitoringframeworkdevelopmentandmodeltesting AT yunprihantinamulyani bayesianbasedprojectmonitoringframeworkdevelopmentandmodeltesting |
_version_ |
1725548701635575808 |