Implementasi Algoritme Improved Particle Swarm Optimization Untuk Optimasi Komposisi Bahan Makanan Untuk Memenuhi Kebutuhan Gizi Penderita Penyakit Diabetes Melitus - Gregorius Dhanasatya Pudyakinarya; Imam Cholissodin; Fitra Abdurrachman Bachtiar (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2018)
Diabetes Mellitus is one of the diseases with the highest number of casualties in Indonesia. The high diabetics in Indonesia are due to the lack of public knowledge about healthy food controls that result in poor diet. As a result, many people have not met the balance of nutritional intake that is the most important part in managing a good and healthy diet. Information on the right diet is needed for diabetics to improve their health condition. The Particle Swarm Optimization (PSO) algorithm is often used in performing optimization cases with good and optimal results, in particular, there is development to Improved Particle Swarm Optimization (IPSO) which further improves PSO performance. Therefore, this study designs an optimization system for the composition of food ingredients for the nutritional needs of people with Diabetes Mellitus using Improved-PSO algorithm. The results obtained from this study are optimized Improved-PSO parameters that are population number = 150, acceleration coefficient value = 2, 1, and convergent system on iteration to 550. In addition, from the results of global analysis shows that the nutrient calculation of the system can meet the nutritional needs of patients with a difference of tolerance Â± 10% of expert calculations.