Penentuan Portofolio Saham Optimal Menggunakan Algoritma Genetika - Rinda Wahyuni; Wayan Firdaus Mahmudy; Budi Darma Setiawan (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2017)
In making investments investors often faced with two things, return expectation and risk rate. Therefore to reduce the risk rate investors diversifying by combining securities in investment, or commonly referred to a stock portfolio. This research implements genetic algorithm to determine the proportion of stocks to generate optimum return expectation with risk rate that can be justified. Based on the test result, genetic algorithm can determine the stocks proportion with greater return expectation and risk rate is smaller than manual calculation using single index model. The largest fitness is 0,356522 in exercise condition of genetic algorithm parameter with population size is 100, the number of generations is 100, crossover rate 0,3, and mutation rate 0,7.