Abstract—The objective of this study is to design a conceptual framework of intelligent human resource management using latent semantic analysis (LSA) with the internet of things (IoT) by using Near Field Communication (NFC) technology and to design the intelligent human resource management architecture using latent semantic analysis with the Internet of Things using NFC. The aim is to develop a prototype in human resource management system development for application in an organization. The research results show that the conceptual framework consists of input in the form of HRM loT LSA. As far as the process is concerned, it was Intelligent Human Resource Management using Latent Semantic Analysis with the Internet of Things to operate in a High Performance Education Organization. The output with regard to the High Performance Education Organization had 4 components: 1) a mobile telephone that had NFC 2) NFC Tag used in imputing the data 3) processing the data by LSA and 4) an application showing the data. The system architecture was divided into 3 main parts: BYOD (Bring Your Own Device), HRM and an HPO Report.
Index Terms—Human resource management, latent semantic analysis, internet of things, NFC.
Kanokrat Jirasatjanukul is with Division of Information and Communication Technology for Education, Faculty of Technical Education, King Mongkut’s University of Technology North Bangkok, Thailand (e-mail: s5902052956011@email.kmutnb.ac.th, jkanokrat@gmail.com). Prachyanun Nilsook is with Vocational Education Technology Research Center, King Mongkut’s University of Technology North Bangkok, Thailand (e-mail: prachyanunn@kmutnb.ac.th). Panita Wannapiroon is with Innovation and Technology Management Research Center, King Mongkut’s University of Technology North Bangkok, Thailand (e-mail: panitaw@kmutnb.ac.th).
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Cite:Kanokrat Jirasatjanukul, Prachyanun Nilsook, and Panita Wannapiroon, "Intelligent Human Resource Management Using Latent Semantic Analysis with the Internet of Things," International Journal of Computer Theory and Engineering vol. 11, no. 2, pp. 23-26, 2019.
