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Vol. 4 No. 01 (2023)

Articles

Salary Prediction for Computer Engineering Positions in India

https://doi.org/10.38094/jastt401140

Published 2023-02-06

  • Ashty Kamal Mohamed Saeed
    • ,
  • Pavel Younus Abdullah
    • ,
  • Avin Tariq Tahir

Ashty Kamal Mohamed Saeed
Ministry of Education, Erbil, Kurdistan Region, Iraq

Pavel Younus Abdullah
Pazmany Peter Catholic University, Budapest, Hungary

Avin Tariq Tahir
University of Miskolc, Miskolc, Hungary

Abstract

Over the subsequent 20 years, India's economy has seen growth in many areas since the 1990s. Information technology is one of the industries that has grown significantly recently. Bharat's transformation from a sluggish economy to one of the top exporters of information technology services has been largely attributed to the information technology sector. Since there was such a huge need for skilled workers in the labor markets as a result of this boom, engineering has consistently ranked among the top high school courses of study. Additionally, engineering is a popular course of study due to the income potential and opportunity to progress technology. The primary compensation factors for recent engineering graduates in the Bharat Labor Markets are the focus of this study. The investigation looked at how factors like as demography, academic success, personality traits, and test scores affected starting pay. The analysis' findings showed that the significant predictors of starting pay were academic success at the faculty level, faculty name, college affiliation, and engineering major. The results also revealed that psychological characteristic skills, such as English and quantitative aptitude, as well as a desire to strive and complete a task well, are significant contributors to the starting pay of engineering graduates in Indian Labor Markets. This study used a machine learning method to carry out regression analysis. These procedures used the Naive Bayes, Random Forest, and Support Vector Machine algorithms (SVM).

 

Keywords

Salary prediction, Support Vector Machine, SVM, Naïve Bayes, Random Forest

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Author Biography

Ashty Kamal Mohamed Saeed

 

 

Pavel Younus Abdullah

 

 

Avin Tariq Tahir

 

 

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