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- W2590586603 abstract "Learning in groups is one of the important things in the learning process. By forming some groups of students, they are able to share and complement deficiency. The best combination of student in a group will give the best result in learning. But to form the groups of students, need much time, because it is a combinatorical problem. To get the best combination, it needs to evaluate all of the possible solutions. Adaptive genetic algorithm (AGA) was used in this paper to find the best group formation. The adaptive number of population, crossover probability, and mutation rate were applied in this paper based on the fitness achieved in each generation. This study used 25 students in Basic Programming class as a data testing and divided them into 5 groups. This paper shown how AGA find the solution of the problem eficiently in time and the fitness value. The maximum of fitness gain by AGA was 86.88% of the actual fitness in the case study." @default.
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- W2590586603 date "2016-09-01" @default.
- W2590586603 modified "2023-09-23" @default.
- W2590586603 title "Student grouping using adaptive genetic algorithm" @default.
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- W2590586603 doi "https://doi.org/10.1109/elecsym.2016.7861034" @default.
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