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Papers by Preenithi Aksorn
Journal of Advances in Information Technology, 2022
The construction industry could not avoid the technology disruptive era. Therefore, the Thai gove... more The construction industry could not avoid the technology disruptive era. Therefore, the Thai government has created a new policy and directed all departments to implement big data technology. Big data technology includes Machine Learning (ML). The present study attempts to predict over-budget construction projects using an ML algorithm. Data were collected from the comptroller general's department of Thailand for over-budget project cases. Information about 692 projects completed in Thailand in 2019, covering all types of construction projects, was collected and analyzed. ML, an analytical technique for big data technology, was used as a tool in this study. In addition, k-Nearest Neighbors (KNN), an ML algorithm, was used to classify over-budget projects. The input data have four attributes: department of project, construction site location, type of project, and methods of procurement; the output is a yes/no decision on whether a project has been over budget. The dataset was preprocessed for analysis and modeled using the KNN function in Python 3. According to the test results, the KNN model achieves an accuracy (precision) of 0.86. Finally, the developed model has demonstrated that it can be used to predict the over-budget construction projects for the Thai government.
MATEC Web of Conferences, 2018
This study aims to apply Exploratory Factor Analysis in government construction procurement probl... more This study aims to apply Exploratory Factor Analysis in government construction procurement problems. The questionnaire used in this study to collect data with is the Cronbach’s Alpha Coefficient equal to 0.986. The data was collected through Web Survey and 353 participants completed the questionnaires. The data was analysed with the use of percentages, mean, standard deviation, and Exploratory Factor Analysis. When ranking the effect of each component on government construction procurement problems, it was found that the most influential component is procurement process problems, followed by internal and external influence problems, and project management and technical problems, respectively. The top 3 detailed problems on government construction procurement were: 1) Problems arising from fix announcement period, 2) Restrictions according to the regulations that all agencies need to send the announcement details by the approval date of procurement, and 3) Problems arising from fix ...
International Journal of Project Organisation and Management, 2016
This research has focused on the practice of life cycle management through the process of communi... more This research has focused on the practice of life cycle management through the process of community infrastructure development in Thailand. The main objective was to identify success factors influencing community infrastructure projects throughout the life cycle. The assessment was based on fresh and thorough informative investigation of the community background. The activities of projects were investigated by documentation, observing and interviewing professional management agencies, government agencies, local governments, and by questing villagers. All contextual conditions relevant to the phenomenon were drawn out and studied carefully. In-depth information that was put into practice was gathered by a multiple case studies investigation in which the semi-structured interview instrument had been illustrated earlier. Triangulation method was used to check and establish validity in the studies by analysing research questions from multiple perspectives. The data was analysed and identified for the precise outcomes. The finding showed 12 key success factors were influenced throughout the life cycle management investigation.
Facilities, 2015
Purpose – This paper aims to identify the critical factors highly influencing sustainability of l... more Purpose – This paper aims to identify the critical factors highly influencing sustainability of local infrastructure projects in the Thai community. Design/methodology/approach – Both qualitative and the quantitative analyses were used when needed to follow the right procedure. Together, the panels of experts, selected from the related fields, were always prompt to cooperate with the strategies upon request. At the early stage, thoroughly fresh and in-depth information, theoretical and practical, in local infrastructure sustainability development, was gathered through literature review, a semi-structure interview and a focussed group meeting. For the pilot project, all crucial attributes were assigned to items of a questionnaire by a representative sample, Huai Hong Khrai Royal Development Study Centre, one of the most important sources in community development in Thailand. Afterward, the improved questionnaires were surveyed for exact data by all target respondents: local infrastru...
Journal of Construction Engineering and Project Management, 2016
Journal of Advances in Information Technology, 2022
The construction industry could not avoid the technology disruptive era. Therefore, the Thai gove... more The construction industry could not avoid the technology disruptive era. Therefore, the Thai government has created a new policy and directed all departments to implement big data technology. Big data technology includes Machine Learning (ML). The present study attempts to predict over-budget construction projects using an ML algorithm. Data were collected from the comptroller general's department of Thailand for over-budget project cases. Information about 692 projects completed in Thailand in 2019, covering all types of construction projects, was collected and analyzed. ML, an analytical technique for big data technology, was used as a tool in this study. In addition, k-Nearest Neighbors (KNN), an ML algorithm, was used to classify over-budget projects. The input data have four attributes: department of project, construction site location, type of project, and methods of procurement; the output is a yes/no decision on whether a project has been over budget. The dataset was preprocessed for analysis and modeled using the KNN function in Python 3. According to the test results, the KNN model achieves an accuracy (precision) of 0.86. Finally, the developed model has demonstrated that it can be used to predict the over-budget construction projects for the Thai government.
MATEC Web of Conferences, 2018
This study aims to apply Exploratory Factor Analysis in government construction procurement probl... more This study aims to apply Exploratory Factor Analysis in government construction procurement problems. The questionnaire used in this study to collect data with is the Cronbach’s Alpha Coefficient equal to 0.986. The data was collected through Web Survey and 353 participants completed the questionnaires. The data was analysed with the use of percentages, mean, standard deviation, and Exploratory Factor Analysis. When ranking the effect of each component on government construction procurement problems, it was found that the most influential component is procurement process problems, followed by internal and external influence problems, and project management and technical problems, respectively. The top 3 detailed problems on government construction procurement were: 1) Problems arising from fix announcement period, 2) Restrictions according to the regulations that all agencies need to send the announcement details by the approval date of procurement, and 3) Problems arising from fix ...
International Journal of Project Organisation and Management, 2016
This research has focused on the practice of life cycle management through the process of communi... more This research has focused on the practice of life cycle management through the process of community infrastructure development in Thailand. The main objective was to identify success factors influencing community infrastructure projects throughout the life cycle. The assessment was based on fresh and thorough informative investigation of the community background. The activities of projects were investigated by documentation, observing and interviewing professional management agencies, government agencies, local governments, and by questing villagers. All contextual conditions relevant to the phenomenon were drawn out and studied carefully. In-depth information that was put into practice was gathered by a multiple case studies investigation in which the semi-structured interview instrument had been illustrated earlier. Triangulation method was used to check and establish validity in the studies by analysing research questions from multiple perspectives. The data was analysed and identified for the precise outcomes. The finding showed 12 key success factors were influenced throughout the life cycle management investigation.
Facilities, 2015
Purpose – This paper aims to identify the critical factors highly influencing sustainability of l... more Purpose – This paper aims to identify the critical factors highly influencing sustainability of local infrastructure projects in the Thai community. Design/methodology/approach – Both qualitative and the quantitative analyses were used when needed to follow the right procedure. Together, the panels of experts, selected from the related fields, were always prompt to cooperate with the strategies upon request. At the early stage, thoroughly fresh and in-depth information, theoretical and practical, in local infrastructure sustainability development, was gathered through literature review, a semi-structure interview and a focussed group meeting. For the pilot project, all crucial attributes were assigned to items of a questionnaire by a representative sample, Huai Hong Khrai Royal Development Study Centre, one of the most important sources in community development in Thailand. Afterward, the improved questionnaires were surveyed for exact data by all target respondents: local infrastru...
Journal of Construction Engineering and Project Management, 2016