Optimasi Komposisi Pakan Burung Lovebird Menggunakan Algoritme Particle Swarm Optimization (PSO) - Mauldy Putra Pratama; Imam Cholissodin; Muhammad Halim Natsir (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2019)
Lovebird is a type of bird that many people have as a pet or for a competition. This bird needs adequate nutrients for survival. In reality, there are many of them that over or low nutrients. This study will discuss about how to optimized the composition feeds of lovebird and minimize the costs without reducing the nutrition. Particle Swarm Optimization (PSO) is one of the optimization methods that used for the formulation process and the composition to keep fulfilling the nutrient needs with minimal cost. The PSO algorithm process starts with the initialization process for position, velocity, pBest values as much as the particles and gBest. Then proceed to update the velocity, position, pBest and gBest as much as the iteration that has been determined. Based on the results of the test that have been done in this study, the writer obtains the optimal parameters such as the number of particles as much as 60, the number of iterations is 600 and the value of coefficient k is 0.3. By using these parameters, the price difference is Rp 5,540.00.