Regression Genetic Algorithm (RGA) Based Approach For Optimizing Bank Deposit

Bank' service and interest rate play an important role to stimulus bank deposit fund. Those variables determine the increase of bank's income. Unfortunately, statistical analysis data application cannot prove it, especially the variable service. The aim of this study is to analyze the correlation between the service and the increase in bank deposit fund. This research used a genetic algorithm to discover correlation of those variables. In the implementation, regression and genetic algorithm (RGA) are combined to analyze the variable service by using population, crossover, and mutation approached. Compare to the regression method only, RGA can prove the correlation. Moreover, the good service greatly increases the bank deposit fund shows that in generation = 229, service = 0, 1181099, and deposit = 98873. It means that a good service toward customer may increase or optimize the amount of bank deposit.