Optimasi Komposisi Makanan Diet Bagi Penderita Hipertensi Menggunakan Algoritme Genetika

Shafaat, Muhammad (2017) Optimasi Komposisi Makanan Diet Bagi Penderita Hipertensi Menggunakan Algoritme Genetika. Sarjana thesis, Universitas Brawijaya.

Abstract

Hipertensi merupakan salah satu sebab utama dari mortalitas dan morbiditas di Indonesia, sehingga masalah klinis penyakit ini yaitu intervensi yang sangat umum dilakukan diberbagai tingkat fasilitas kesehatan. Bagi penderita Hipertensi sebaiknya mengatur menu makanannya untuk menghindari dan membatasi makanan yang dapat meningkatkan tekanan darah, untuk itu diperlukan diet untuk mengendalikan kadar gula darah pada penderita hipertensi yaitu dengan cara mengatur komposisi pola makanannya. Salah satu teknik yang digunakan untuk mengatur komposisi makanan diet bagi penderita Hipertensi yaitu dengan pendekatan Algoritme genetika. Data yang digunakan pada penelitian ini adalah data makanan pokok sebanyak 24 jenis dengan masing-masing berat sebesar 180 gram, sumber nabati sebanyak 21 jenis dengan masing-masing berat 50 gram, sumber protein hewani sebanyak 27 dengan masing-masing berat 80 gram, sayuran sebanyak 25 jenis makanan dengan masing-masing berat 200 gram, dan buah-buahan sebanyak 14 jenis dengan masing-masing berat 150 gram. Proses Algoritme genetika menggunakan representasi bilangan integer dengan panjang kromosom 105, setiap gen dari populasi merupakan nomor makanan dari setiap kelompok dan setiap index dari kelipatan 15 merepresentasikan hari, metode crossover yang digunakan yaitu extended intermediate crossover, sedangkan metode mutasi yang digunakan yaitu reciprocal exchange mutation, dan metode seleksi dengan seleksi elitsm. Hasil parameter yang optimal diperoleh pada pengujian jumlah populasi adalah 80 dengan nilai fitness 1100.495433, jumlah generasi adalah 300 dengan nilai fitness 1190.022286, dan kombinasi cr dan mr adalah 0.1 dan 0.9 dengan nilai fitness 1150.466927. Hasil solusi yang diberikan berupa menu rekomendasi makanan untuk beberapa hari kedepan dengan waktu pagi, siang, dan malam serta dengan biaya yang minimal.

English Abstract

Hypertensive is one of the main causes of mortality and morbidity in Indonesia. as the result that, the clinical problems of the disease that is interventions which at various levels of health facilities are commonly done. For people with hypertension should be arranging their food menu to avoid and confine foods that can increase blood pressure. Therefore, it needed a diet to control the blood sugar levels in hypertensive patients by regulating the composition of the diet. One of techniques that is used to manage regulate the composition of diet foods for hypertensive patients used by genetic algorithm approach. The data used in this study is the 24 species of staple food with each weight 180 gram, 21 species of vegetables sources with each weight 50 gram, 27 source of animal protein with each weight 80 gram, 25 kinds of vegetables with each Weight 200 grams, and 14 species of fruit with each weight 150 grams. The genetic algorithm process uses the representation of the integer with the length of chromosome 105 in which each gene of the population is the food number in each group and each index with multiples 15 represents of the day, The crossover method that is used the extended intermediate crossover, while the mutation method that is used reciprocal exchange mutation, and the selection method with elitsm selection. The optimal parameter results obtained on the test population number is 80 with the fitness value 1100.495433, the number of generations is 300 with the fitness value 1190.022286, and the combination of cr and mr is 0.1 and 0.9 with the fitness value 1150.466927. The results of the solution given in the form of food menu recommendations for few days for morning, noon, and night time and with minimal cost.

Item Type: Thesis (Sarjana)
Identification Number: SKR/FTIK/2017/381/051706894
Uncontrolled Keywords: Diet, Hipertensi, Optimasi, Algoritme Genetika,
Subjects: 000 Computer science, information and general works > 004 Computer science > 004.015 1 Finite mathematic
Divisions: Fakultas Ilmu Komputer > Teknik Informatika
Depositing User: Budi Wahyono Wahyono
Date Deposited: 22 Aug 2017 02:42
Last Modified: 09 Dec 2020 15:57
URI: http://repository.ub.ac.id/id/eprint/1478
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