Genetic Algorithms to Optimizatize Lecturer Assessment's Criteria

International Conference on Environment and Technology 2017

生态环境科学

Jollyta, Deny^1 ; Johan, J.^1 ; Hajjah, Alyauma^1

STIKOM Pelita Indonesia Pekanbaru, Riau, Indonesia^1

关键词: Assessment criteria;    Binary;    College;    Fitness functions;    Genetic operators;    Initial population;    Nonlinear problems;    Optimum criteria;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/97/1/012005/pdf
DOI  :  10.1088/1755-1315/97/1/012005

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

The lecturer assessment criteria is used as a measurement of the lecturer's performance in a college environment. To determine the value for a criteriais complicated and often leads to doubt. The absence of a standard valuefor each assessment criteria will affect the final results of the assessment and become less presentational data for the leader of college in taking various policies relate to reward and punishment. The Genetic Algorithm comes as an algorithm capable of solving non-linear problems. Using chromosomes in the random initial population, one of the presentations is binary, evaluates the fitness function and uses crossover genetic operator and mutation to obtain the desired crossbreed. It aims to obtain the most optimum criteria values in terms of the fitness function of each chromosome. The training results show that Genetic Algorithm able to produce the optimal values of lecturer assessment criteria so that can be usedby the college as a standard value for lecturer assessment criteria.