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Anandita Azharunisa Sasmito
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Penerapan Parallel Genetic Algorithm untuk Optimasi Penyusunan Bahan Makanan Keluarga Penderita Hiperkolesterolemia Anandita Azharunisa Sasmito; Imam Cholissodin; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Cholesterol is a fatty substance that is essential for the sustainability of body functions. However, if cholesterol is above normal levels, the body can not eliminate it and will accumulate in the arteries that can cause heart attacks or strokes. A person with hypercholesterolaemia should maintain a diet and nutritional intake. The composition of food consumed should be in accordance with the needs. Unfortunately, few Indonesians realize the importance to pay attention to the diet and nutritional content of the food consumed each day. The algorithm to be used in this research is parallel genetic algorithm (PGA) where the algorithm is the result of modification of the genetic algorithm. In the PGA population will be divided into several sub-populations that run in parallel. In this study PGA still uses the concept of multi-population and migration but will only run on a single processor. In the application of parallel genetic algorithm for this research resulted the highest fitness solution using method parameter with popsize number of 65, sub population of 5, using generation 60, crossover rate with value 0,4 and mutation rate equal to 0,6, Permutation with value 145.
Co-Authors Imam Cholissodin Sutrisno Sutrisno