Optimasi Formulasi Pakan pada Proses Budidaya Ikan Bandeng Menggunakan Particle Swarm Optimization (PSO) - Denny Irfan Darmawan; Imam Cholissodin; Candra Dewi (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
Milkfish is a cultivation commodity that contributes quite large on a national scale. But in practice, milkfish cultivation requires high production costs, especially in the procurement of fish feeds. This study will explore how to optimize the composition of milkfish feeds, minimize costs without lowering the production, as well as keeping the nutritional needs of milkfish in check. An optimization method, Particle Swarm Optimization (PSO) is used in the process of formulation and composition of milkfish feeds to keep fulfilling the nutritional needs of fish with minimal cost. The PSO algorithm process begins with initialization process for position, speed, and Pbest values ​​as much as the number of specified particles, and Gbest. Then the process progresses to the update stage of speed, position, Pbest, and Gbest as much as a predetermined iteration. Based on the results of the tests conducted in this study, optimal parameters have been obtained such as the number of particles as much as 100, the number of iterations of 70, lower boundary value and upper limit particles of 1,0 - 9,0, and coefficient value of 0,4. Using these parameters, the best fish feeds composition obtained for 10-week-old milkfish with a weight per unit of 0,25 kilograms and total fish population of 500 is 0,237 kilograms fish meal, 1,384 kilograms cassava flour, and 2,129 kilograms white leadtree leaf flour with total cost of Rp. 15.017,625.