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Using Text Mining and Tokenization Analysis to Identify Job Performance for Human Resource Management at the University of Phayao

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Recent Challenges in Intelligent Information and Database Systems (ACIIDS 2023)

Abstract

A significant problem in many Thai university organizations is the inability to effectively identify employees’ roles and functions. This research aims to study the workload management of university personnel by text mining techniques. There are two main research objectives. The first objective is to manipulate highly complex Thai word segmentation. The second objective is to produce a predictive model for identifying job performance for human resource management of university personnel. Research tools are machine learning algorithms and word segmentation analysis, including Decision Tree (DT), Generalized Linear Model (GLM), K-Nearest Neighbors (K-NN), Naïve Bayes (NB), Support Vector Machine (SVM), Term Frequency-Inverse Document Frequency (TF-IDF), Term Frequency (TF), Term Occurrences (TO), and Binary Term Occurrences (BTO) techniques. The research data is compiled from job descriptions for three positions from the School of Information and Communication Technology at the University of Phayao. The results show that the best predictive model is developed with the Generalized Linear Model (GLM). It has a high accuracy value of 89.80%, with Binary Term Occurrences (BTO) technique. Research operational plan for future work, researchers plan to develop an information system to support work within the School of Information and Communication Technology, University of Phayao to support further work.

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Acknowledgements

This research project was supported by the Thailand Science Research and Innovation Fund and the University of Phayao (Grant No. FF66-UoE002). In addition, this research was supported by many advisors, academics, researchers, students, and staff. The authors would like to thank all of them for their support and collaboration in making this research possible.

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Correspondence to Pratya Nuankaew .

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Nuankaew, W.S., Thipmontha, R., Jeefoo, P., Nasa-ngium, P., Nuankaew, P. (2023). Using Text Mining and Tokenization Analysis to Identify Job Performance for Human Resource Management at the University of Phayao. In: Nguyen, N.T., et al. Recent Challenges in Intelligent Information and Database Systems. ACIIDS 2023. Communications in Computer and Information Science, vol 1863. Springer, Cham. https://doi.org/10.1007/978-3-031-42430-4_47

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  • DOI: https://doi.org/10.1007/978-3-031-42430-4_47

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-031-42430-4

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