Sasmito, Anandita Azharunisa (2017) Penerapan Parallel Genetic Algorithm Untuk Optimasi Penyusunan Bahan Makanan Keluarga Penderita Hiperkolesterolemia. Sarjana thesis, Universitas Brawijaya.
Abstract
Kolesterol merupakan zat lemak yang penting untuk keberlangsungan fungsi tubuh. Namun jika kolesterol berada pada jumlah diatas normal maka tubuh tidak bisa menghilangkannya dan akan menumpuk pada arteri yang dapat menyebabkan serangan jantung atau stroke. Seorang penderita hiperkolesterolemia harus menjaga pola makan dan asupan gizinya. Komposisi makanan yang dikonsumsi harus sesuai dengan kebutuhan. Sayangnya penduduk Indonesia sedikit yang menyadari pentingnya untuk memperhatikan pola makan dan kandungan gizi dari makanan yang dikonsumsi setiap harinya. Algoritme yang akan digunakan pada penelitian kali ini adalah parallel genetic algorithm (PGA) di mana algoritme ini merupakan hasil modifikasi dari algoritme genetika. Pada PGA populasi akan terbagi menjadi beberapa sub-populasi yang berjalan secara parallel. Pada penelitian kali ini PGA tetap menggunakan konsep multi populasi dan migrasi namun hanya akan dijalankan pada prosessor tunggal. Pada penerapan parallel genetic algorithm untuk penelitian ini menghasilkan solusi dengan fitness paling tinggi menggunakan parameter metode dengan jumlah popsize sebanyak 65, sub populasi sebesar 5, menggunakan generasi sebanyak 60, crossover rate dengan nilai 0,4 dan mutation rate sebesar 0,6, dan batas permutasi dengan nilai 145.
English 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.
Item Type: | Thesis (Sarjana) |
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Identification Number: | SKR/FTIK/2017/640/051708152 |
Uncontrolled Keywords: | Parallel Genetic Algorithm, Hiperkolesterolemia, Bahan Makanan |
Subjects: | 000 Computer science, information and general works > 004 Computer science > 004.015 1 Finite mathematic |
Divisions: | Fakultas Ilmu Komputer > Teknik Informatika |
Depositing User: | Yusuf Dwi N. |
Date Deposited: | 09 Oct 2017 06:28 |
Last Modified: | 06 Dec 2020 03:40 |
URI: | http://repository.ub.ac.id/id/eprint/3426 |
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