Analysis and development of the ProTrack application: construction timeline management using Extreme Programming Methodology
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The Evaluation and Adaptation phase in developing the ProTrack application using the Extreme Programming (XP) Method reflects the adaptive approach's success in ensuring the application's quality and relevance as it evolves. The research method involved a structured survey to gather feedback from users and stakeholders, involving 45 respondents from construction company employees. The survey results showed that 78% of the respondents found significant benefits in managing projects through the app's features. Furthermore, the performance and security evaluation process through thorough testing resulted in an 18% decrease in application response time and a 12% increase in data security. The app successfully improved its performance and integrity through cyber risk prevention measures and code optimization. An essential contribution of this research is seen in the successful development and testing of the ProTrack application with XP's adaptive approach to construction project management. The research results provide valuable insights for developers and practitioners in technology and project management, particularly in the face of the complex dynamics of the construction industry. The research generated a deeper understanding of user perceptions and needs by relying on survey feedback data, enabling continuous application improvement. The research confirmed the effectiveness of the XP-based adaptive approach in producing a responsive and effective application solution capable of adapting to rapid changes in the dynamic construction project environment.
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Akhtar, A., Bakhtawar, B., & Akhtar, S. (n.d.). EXTREME PROGRAMMING VS SCRUM: A COMPARISON OF AGILE MODELS. International Journal of Technology, Innovation and Management (IJTIM), 2, 2022. https://doi.org/10.54489/ijtim.v2i1.77
Alzahrani, J. I., & Emsley, M. W. (2013). The impact of contractors ’ attributes on construction project success?: A post construction evaluation. JPMA, 31(2), 313–322. https://doi.org/10.1016/j.ijproman.2012.06.006
Aulawi, H., Nuraeni, F., Setiawan, R., Rianto, W. F., Surya Pratama, A., & Maulana, H. (2023a). Simple Additive Weighting in the Development of a Decision Support System for the Selection of House Construction Project Teams. 2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE), 517–522. https://doi.org/10.1109/ICCoSITE57641.2023.10127813
Aulawi, H., Nuraeni, F., Setiawan, R., Rianto, W. F., Surya Pratama, A., & Maulana, H. (2023b). Simple Additive Weighting in the Development of a Decision Support System for the Selection of House Construction Project Teams. 2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE), 517–522. https://doi.org/10.1109/ICCoSITE57641.2023.10127813
Awad, A., & Fayek, A. R. (2012). A decision support system for contractor prequalification for surety bonding. In Automation in Construction (Vol. 21, Issue 1, pp. 89–98). Elsevier B.V. https://doi.org/10.1016/j.autcon.2011.05.017
Chen, J., Yu, T., Yin, L., Tang, J., & Wang, H. (2020). A unified time scale intelligent control algorithm for microgrid based on extreme dynamic programming. CSEE Journal of Power and Energy Systems, 6(3), 583–590. https://doi.org/10.17775/CSEEJPES.2019.00100
Domingues, L., & Ribeiro, P. (2023). Project Management Maturity Models: Proposal of a Framework for Models Comparison. Procedia Computer Science, 219, 2011–2018. https://doi.org/10.1016/j.procs.2023.01.502
Guraziu, E., & Gobbo, G. Del. (2023). An emerging qualitative study on Project management as a bridge between cognitive learning and employability. Procedia Computer Science, 219, 1954–1962. https://doi.org/10.1016/j.procs.2023.01.495
Gutierrez, G., Garzas, J., De Lena, M. T. G., & Moguerza, J. M. (2019). Self-Managing: An Empirical Study of the Practice in Agile Teams. IEEE Software, 36(1), 23–27. https://doi.org/10.1109/MS.2018.2874324
Jean Cross Sihombing, D., Joko Santoso, A., & Rahayu, S. (n.d.). Model Perangkingan Proyek Kontruksi pada Asosiasi Kontraktor Menggunakan Fuzzy AHP. Scientific Journal of Informatics, 2(1). http://journal.unnes.ac.id/nju/index.php/sji
Marzouk, M. M. (2011). Automation in Construction ELECTRE III model for value engineering applications. Automation in Construction, 20(5), 596–600. https://doi.org/10.1016/j.autcon.2010.11.026
Montalbán-Domingo, L., Casas-Rico, J., Alarcón, L. F., & Pellicer, E. (2023). Influence of the experience of the project manager and the foreman on project management’s success in the context of LPS implementation. Ain Shams Engineering Journal, 102324. https://doi.org/10.1016/j.asej.2023.102324
Nguyen, P. H. D., & Robinson Fayek, A. (2022). Applications of fuzzy hybrid techniques in construction engineering and management research. Automation in Construction, 134, 104064. https://doi.org/10.1016/j.autcon.2021.104064
Pan, N. (2008). Fuzzy AHP approach for selecting the suitable bridge construction method. Automation in Construction, 17(8), 958–965. https://doi.org/10.1016/j.autcon.2008.03.005
Reis, I., & Ribeiro, P. (2023). A Singular Environment: Featuring a Framework for Integrated Project Management. Procedia Computer Science, 219, 2019–2026. https://doi.org/10.1016/j.procs.2023.01.503
Rocha, A., Romero, F., Miranda, D., Amorim, M., & Lima, R. M. (2023). Quality management practices to direct and control the accomplishment of project objectives in R&D units. Procedia Computer Science, 219, 36–43. https://doi.org/10.1016/j.procs.2023.01.261
Saad, S., Alaloul, W. S., Ammad, S., Altaf, M., & Qureshi, A. H. (2022). Identification of critical success factors for the adoption of Industrialized Building System (IBS) in Malaysian construction industry. Ain Shams Engineering Journal, 13(2), 101547. https://doi.org/10.1016/j.asej.2021.06.031
Santos, J. I., Pereda, M., Ahedo, V., & Galán, J. M. (2023). Explainable machine learning for project management control. Computers and Industrial Engineering, 180. https://doi.org/10.1016/j.cie.2023.109261
Serpell, A., & Rubio, H. (2023). Evaluating project management (PM) readiness in construction companies: cases from Chile. Procedia Computer Science, 219, 1642–1649. https://doi.org/10.1016/j.procs.2023.01.457
Yang, P., Liu, Z., Xu, J., Huang, Y., & Pan, Y. (2020). An Empirical Study on the Ability Relationships between Programming and Testing. IEEE Access, 8, 161438–161448. https://doi.org/10.1109/ACCESS.2020.3018718
Zulfiandri, Yasmin, F. D., & Kusumaningtyas, R. H. (2022). Implementation of Critical Path Method and What If Analysis in Project Management Information System. 2022 10th International Conference on Cyber and IT Service Management (CITSM), 1–6. https://doi.org/10.1109/CITSM56380.2022.9935912
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