Turbines installed in farming have slightly different characteristics. Mainly the problem is when several tidal turbines are placed side by side at the location of the tidal current flow. Therefore, is it necessary to predict energy at specific marine locations or to optimize the arrangement of turbines. The farm layout is precisely arranged to obtain the best position. One of the stages of optimizing turbines is the effective placement of turbine configuration using the Particle Swarm optimization (PSO) algorithm. This method is suitable for solving turbine positioning problems. This study aims to optimize position optimization to obtain the maximum power and minimum cost per power of the turbine using the PSO algorithm. The optimization of 2D position in three different scenarios has a substantial impact on the spacing between turbines and effects of objective function. The results of case 3 have a higher objective function value than cases 1 and 2, with an objective function value of 2.330 for five turbines and 1.415 for ten. The result shows turbine arrangement, the three cases show the influence of the current direction from various directions showing positions that are more spread out and pointing in identical directions but do not significantly affect the power generated. Speed has a significant effect on the power produced by the turbine. Variations in direction cause the position of the turbine to spread, while at an identical speed in one direction, the turbine's position is directed in that direction. The PSO method can produce optimal solutions at a cost per product in complex environments with varying directions and speeds in actual circumstances.