Enhanced Recursive Feature Selection Method for Analyzing Critical Factors in Enterprise Resource Planning Implementation

• Published in: 2022 6th International Conference on Trends in Electronics and Informatics (ICOEI) pp. 1674 - 1678
• Main Authors: Christy, A., Praveena, M.D. Anto, Helen, Suji, Jesudoss, A., Theresa, M. Mercy
• Format: Conference Proceeding
• Language: English
• Published: IEEE 28.04.2022
• Subjects: COST; Costs; Enterprise resource planning; ERP; etc; Feature extraction; Feature Selection; Genetic algorithm; Linear Regression; Manuals; Productivity; Software
• DOI: 10.1109/ICOEI53556.2022.9777211

Enterprise Resource Planning (ERP) are programmed for institutionalizing, streamlining and coordinating business forms crosswise over various account, acquisitions, for circulation purpose, and for other different divisions. The day e-organizations have begun to rise, organizations are following the ways to be progressively profitable. The objective of this paper is to optimize the critical factors such as cost and time in various ERPs. In this paper, the Enhanced Recursive Feature Elimination method has been proposed for feature selection. Modeling of ERP parameters such as Design of Experiments (DoE) and Response Surface Methodology (RSM) are done with linear regression and the significance of the model is studied using ANOVA table. Feature selection is done also done using Genetic algorithm. Comparisons are made between Manual planning and Genetic algorithm based Recursive Feature selection method and experimental results have shown ERP cost can be reduced to 40% by adopting the proposed approach.