Kushardiana, Resthy (2013) Penentuan Komposisi Menu Makanan Untuk Penderita Diabetes Mellitus Menggunakan Algoritma Genetika. Sarjana thesis, Universitas Brawijaya.
Abstract
Indonesia merupakan salah satu negara dengan jumlah penderita diabetes terbanyak di dunia. Sampai dengan tahun 2008, Departemen Kesehatan Republik Indonesia mencatat Indonesia sebagai peringkat ke-4 di dunia yaitu 5,6%. Pada penyakit Diabetes Mellitus, diet merupakan pengobatan paling mendasar melalui kombinasi dalam penyusunan menu makanannya. Penyusunan komposisi menu makanan termasuk dalam suatu permasalahan kombinatorik dan dapat diselesaikan dengan algoritma genetika. Sesuai struktur umum dari algoritma genetika, data bahan makanan dikombinasikan menjadi individu yang merupakan 1 kesatuan menu dalam sehari dan akan dievaluasi menggunakan sebuah fungsi evaluasi (fungsi fitness). Dari hasil pengujian yang dilakukan, didapatkan bahwa nilai probabilitas crossover yang terlalu rendah atau terlalu tinggi mengakibatkan fitness yang buruk. Sedangkan jumlah populasi dan generasi yang semakin tinggi, cenderung menghasilkan fitness yang baik. Dari beberapa hasil pengujian, dapat dihasilkan solusi lokal optimum dengan nilai fitness maksimum yaitu 1,0 sehingga sistem dikatakan dapat diimplementasikan untuk menghasilkan kombinasi menu dan berat makanan dalam sehari sesuai dengan kebutuhan tubuh penderita Diabetes Mellitus.
English Abstract
Indonesia is one of the countries which have the highest number of diabetics in the world. In 2008, the Ministry of Health of Republic of Indonesia noted that Indonesia was ranked the fourth in the world approximately 5.6%. In diabetes mellitus, diet is a fundamental treatment through healthy food combination. Composing the menu is one of the combinatory problems and can be solved using genetic algorithm. According to the common structure of genetic algorithm, foodstuff data is compounded as individual which formed one menu combination in a day and will be evaluated using fitness function formula. The testing result show that a too high or low crossover probability will bring out the bad fitness. Meanwhile, the higher the value of population and generation amount tends to give the better fitness. From several testing, the optimum local is reached with the maximum value of fitness 1.0, thus this system can be implemented to result the menu and weight food combination in one day according to diabetic body requirement.
| Item Type: | Thesis (Sarjana) |
|---|---|
| Identification Number: | SKR/FTIK/2013/4/051300934 |
| Subjects: | 000 Computer science, information and general works > 005 Computer programming, programs, data |
| Divisions: | Fakultas Ilmu Komputer > Teknik Informatika |
| Depositing User: | Hasbi |
| Date Deposited: | 28 Mar 2013 09:52 |
| Last Modified: | 23 Oct 2021 09:47 |
| URI: | http://repository.ub.ac.id/id/eprint/145827 |
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