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All Journal Jurnal Teknik Industri : Jurnal Hasil Penelitian dan Karya Ilmiah dalam Bidang Teknik Industri
Akinyokun, Olusina Temidayo
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Computer Science & IT Decision Sciences, Operations Research & Management Engineering Environmental Science Industrial & Manufacturing Engineering

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A Review of the Application of Decision Tree Analysis and Artificial Neural Networks in Project Management Akinyokun, Olusina Temidayo; Morakinyo Kehinde, Onifade.; Abejide, Adegoke Michael
JTI: Jurnal Teknik Industri Vol 11, No 1 (2025): JUNI 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/jti.v11i1.16480

Abstract

The advancement of computing and communication technologies has fueled the growth of Information Technology (IT), with Artificial Intelligence (AI) emerging as a transformative force in modernizing project management practices. This study explores the application of two prominent AI techniques—Decision Tree Analysis (DTA) and Artificial Neural Networks (ANN)—in improving project planning and control. A review of empirical studies highlights the limitations of conventional tools such as Gantt charts and the Critical Path Method (CPM) in managing complex project variables, often resulting in cost overruns and schedule delays. In contrast, DTA and ANN demonstrate superior predictive accuracy, decision support, and adaptability capabilities. DTA offers transparent and structured decision-making models, while ANN excels in pattern recognition and outcome forecasting. The findings underscore that integrating these AI tools enhances project efficiency, cost estimation, and time management, establishing AI as a critical asset for future project success.Keywords: Artificial Intelligence, Decision Tree Analysis, Artificial Neural Networks, Project Planning, Project Control
Co-Authors Abejide, Adegoke Michael Morakinyo Kehinde, Onifade.