Prediction of UPSR Result using clonal selection algorithm (PUR) / Muhammed Khaleeq Shafii

Prediction of UPSR Result system is one of application in predicts the grades of students in the future. This system inspired from Immune System based on virus insert into body. The problem statement of this research is still using manual system such as Microsoft Excel to calculate the grade to predict of UPSR result, sometimes existing system have mistaken calculating and produce accurate grade and a longer time to determine each student’s grade. It consists of a combination of two examinations data taken from school in Kelantan. Prediction of UPSR Result system is a difficult task because it involves a large number of constraints. In Sekolah Kebangsaan Mentuan, school has problems on produce grade because it is using manually and takes time. This project highlights the prediction of UPSR Results system development using Artificial Immune System (AIS) at their school. This project focuses on three main objectives to investigate the UPSR Examination of data for prediction result, to study the Clonal Selection algorithm of the term and to develop the Prediction of UPSR Result System using Clonal Selection Algorithm. Clonal selection algorithm (CLONALG) in AIS is one of the proposed methods to be obtained in real UPSR. Evaluation conducted in this project has shown 79% accuracy. This project can be improved by making a comparative study on Artificial Immune System and other techniques or algorithms used to predict future grade students in UPSR examination. In order to improve the ability of the prototype of this project, some modification and enhancement could be done. It can be improved based on data set. This project also can be improved by make a comparative study on Artificial Immune System and other techniques or algorithms that can be used to solve predict actual UPSR grade. This would give a brief overview on which techniques or algorithms give better optimization and faster results in generating Prediction of UPSR result. Recommendations have been made based on the prototypes abilities and weaknesses so that an improvement can be done to give optimize output in generating Prediction of UPSR Result system.