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Jofanza Denis Aldida
Universitas PGRI Madiun
Computer Science & IT

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Particle Swarm Optimization-based Linear Regression for Software Effort Estimation Puguh Jayadi; Khairul Adilah binti Ahmad; Rayhan Zulfitri Dwi Cahyo; Jofanza Denis Aldida
Journal of Information System, Technology and Engineering Vol. 2 No. 2 (2024): JISTE
Publisher : Yayasan Gema Bina Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61487/jiste.v2i2.69

Abstract

In the context of software effort estimation, this study investigates the use of Particle Swarm Optimization (PSO)-based Linear Regression to improve estimation accuracy. The main problem faced is the limitations of standard Linear Regression models in accurately estimating the effort required for software development projects. This research aims to improve the quality of estimation of software efforts to optimize resource management and project schedules. The method used was the integration of PSOs in Linear Regression, which was evaluated using three different COCOMO datasets. Experimental results show that LR+PSO models consistently outperform standard Linear Regression with lower MAE, MSE, and RMSE, as well as higher R-squared. In conclusion, integrating PSOs in Linear Regression effectively improves the estimation accuracy of software efforts, demonstrating great potential for improving estimation quality in software project management practices.
Co-Authors Khairul Adilah binti Ahmad Puguh Jayadi Rayhan Zulfitri Dwi Cahyo