Abstract
Higher education management problems in delivering 100% of graduates who can satisfy business demands. In industry it is often difficult for qualified graduates to identify the appropriate means to evaluate problem - solving abilities as well as shortcomings in the evaluation of problem solving skills. This is partially due to the lack of an adequate methodology. The purpose of this paper is to provide the appropriate CBR-KBS model for predicting and evaluating the characteristics of the student's dataset so as to comply with the parameters of selection required by the university industry. Machine learning algorithms have been used in these study areas under supervision, uncompleted and uncontrolled; K-Nearest neighbor, Naïve Bayes, Decision Tree, Neural Network, Logistic Regression and Vector Support Machines. The proposed model would allow university management to make easier, more professional, experienced and industry-specific plans for the manufacturing of graduates and graduates who passed the type I and II examinations held by the employment opportunities.
Highlights
Graduates have raised their rate of unemployment from one year to the
It is very difficult to know how qualified graduates appear for college, even though this field is not explored [1]
The survey conducted by Kementerian Pengajian Tinggi in 2014 included 88.7% working in full time and 11.3% worked in part-time
Summary
Graduates have raised their rate of unemployment from one year to the next. A total of 200,000 university graduates graduated annually. Many surveys have been conducted to identify the pattern in graduates' productivity and job status [2] One of these is the analysis of the graduate tracer by the higher education department. According to information from the Ministry of Higher Education, a total of 28,148 people have graduations and their proportion have not been at public university, compared with 52,219 graduates in their entirety from the group of institutions of higher education; (HEIs). This is a very worrying figure, given that the results suggest that the highest unemployment rate is for unemployed graduates from public universities. Any data mining algorithm is provided with a machine learning category and different data mining algorithms are used to set knowledge-based data [7]
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