The Entry Qualifications and Gender Analysis of Student Performance by using Artificial Intelligent Method

Entry qualifications are very important for the educational institution or educational providers to ensure quality graduate been produced. This paper presents the influence of gender, entry qualification and entry results towards the student performance in university. Total of 65 students were randomly selected in faculty of mechanical engineering, University Malaysia Pahang. Entries qualifications are from Foundation Program, Higher Certificate of Malaysian Education (STPM) and Diploma Certificate. STPM is form six examinations in secondary school level. Multilayer Perceptron Neural Network (MPNN) method was used to measure and predict the student’s performance. Result from the study shows that gender not significant role but entry results plays important role. Good entry results student normally maintain their performance throughout the study and become excellent graduates. MPNN is an important tool to study the different type of variables for student performance