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Calculating Student Performance of Jagannath University Using Artificial Neural Network

Md. Tanjil Sarker, Md. Al Mamun Sarker, Dr. Uzzal Kumar Acharjee

In this paper an Artificial Neural Network (ANN) display, for estimating the execution of a sophomore understudy selected in designing majors in the Faculty of Science in Jagannath University of Bangladesh was created and tried. Various variables that may conceivably impact the execution of an understudy were illustrated. Such elements as higher secondary school score, score of subject, for example, Math I, Math II, Electrical Circuit I, and Electronics I taken amid the understudy first year, number of credits passed, understudy aggregate review point normal of first year, sorts of secondary school went to and gender orientation, among others, were then utilized as information factors for the ANN demonstrate. A model in light of the Multilayer Perceptron Topology was created and prepared utilizing information spreading over five eras of alumni from the Computer Science and Engineering Department of the Jagannath University, Dhaka Bangladesh. Test information assessment demonstrates that the ANN model can effectively foresee the execution of over 80% of forthcoming understudies.