SVM and RF Based Performance Enhancement in Organization: A Study on KGI, Odisha and its Organizational Growth
Barsha Baishali Sahoo, Snehasis Dey
Journal of Engineering Research and Reports · pp. 190–197 · Published 21 May 2024
10.9734/jerr/2024/v26i61173Abstract
Organization and organizational growth are two important aspects of a society and its relevant advancement. Now along with organization and its growth, the society advancement becomes most priority for the new age. Technologies that are becoming essential for these growths must have to be inculcated in new age society for complete advancement. Artificial intelligence, machine learning and deep learning are taking industry in a different horizon for complete globalization and adequate smarter than ever before. This paper dives into the organizational growth in particular having studied different aspects of making it even better and implementing different algorithms of AI/ML technologies to provide the best result for organizational growth. The Industry 4.0 has paved the way to build a strong organizational infrastructure for its sustainability in this competitive scenario. It is continuously leveraging different technologies and techniques to strengthen the growth. The next step is to adapt to the Industry 5.0 which works only with efficient robots and quantum computations. Researchers are searching and implementing every possible algorithm to its current infrastructure so as to produce effective results and methodologies that are best suited for fetching higher productivity. Artificial intelligence and Machine learning has produced immense growth in organizational success in recent times. The detailed study of Machine learning based algorithms in organizational growth is rapidly increasing in current years. Basically resource management, staff selection, training, monitoring and data analysis in an organization can be implemented with Machine learning algorithms for its complete growth. The challenge is to choose the proper algorithm from a specific learning technique and properly implementing it to the organization’s different aspects. In this paper basically Support vector machine (SVM) and random forest (RF) algorithms are analyzed and implemented to the specific organization KGI for effective resource management. The result is compared to get best suitable organizational infrastructure that is suited for industry 4.0.
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