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An Effective Model for Choosing Career in Schools using Data Mining Techniques

R. Thirumalaiselvi *, P. Narayanan**

*-** Department of Computer Science, Government Arts College for Men, Chennai, Tamil Nadu, India.

Periodicity:January - March'2021
DOI : https://doi.org/10.26634/jse.15.3.18319

Abstract

An increasing number of future labour force will not just comprise highly skilled human resources, but would also seek to hire personnel with sound technical, analytical, and soft skills to get engaged in cross-cultural and multi-lingual organizational setup. The major challenge of higher education is the lack of knowledge of the talents of students, so their chances of success decreases. Choosing a wrong course leads to incompletion and getting a job becomes tougher. Predicting student skills early can help mentors to advice students in a timely manner and improve student success. In this paper, a model has been created using Naïve Bayes, J48, Random Forest, and Support Vector Machine (SVM) classification algorithm, with 100 attributes. Among the models built, Naïve Bayes and Random Forest algorithm yielded better accuracy rating. In this research work, we attempt to explore dynamic dataset by applying data mining methods to explore student's insights based on characteristics related to academic, technical, environment and interpersonal factors. The model has been tested and found to be performing well in constraint based learning environment.

Keywords

Classification, Decision Tree, Prediction, Identification, Random Forest, Visualization.

How to Cite this Article?

Thirumalaiselvi, R., and Narayanan, P. (2021). An Effective Model for Choosing Career in Schools using Data Mining Techniques. i-manager's Journal on Software Engineering, 15(3), 21-28. https://doi.org/10.26634/jse.15.3.18319

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