Larasati, Shinta Anggun (2018) Optimasi Komposisi Makanan Bagi Penderita Obesitas Pada Orang Dewasa Menggunakan Algoritme Particle Swarm Optimization (PSO). Sarjana thesis, Universitas Brawijaya.
Abstract
Obesitas terjadi disebabkan adanya penumpukan lemak dalam tubuh yang sangat tinggi. Sehingga menyebabkan berat badan menjadi tidak ideal. Obesitas juga dapat menimbulkan komplikasi penyakit, beberapa diantaranya dapat membahayakan nyawa. Penderita perlu mengendalikan banyaknya asupan makanan untuk mendapatkan berat badan ideal dan pengeluaran biaya minimum yaitu dengan cara mengatur komposisi makanan yang masuk kedalam tubuh. Penelitian ini dilakukan dengan cara optimasi komposisi makanan bagi penderita obesitas pada orang dewasa menggunakan algoritme Particle Swarm Optimization (PSO). Dalam penelitian ini, pembentukkan partikel awal dilakukan secara acak berdasarkan jumlah makanan yang ada sehingga tidak perlu diubah ke dalam indeks makanan. Hasil dari penelitian ini berupa berat badan aktual, berat badan ideal, status gizi, kebutuhan energi, kebutuhan protein, kebutuhan lemak dan kebutuhan karbohidrat. Pengujian dari penelitian ini menghasilkan parameter yang optimal antara lain jumlah partikel = 80, jumlah iterasi berdasarkan uji konvergensi sebesar 703,
English Abstract
Obesity occurs due to buildup of fat in the body is very high. Thus causing weight gain be not ideal. Obesity can also cause disease complications, some of which can endanger lives. To get the ideal body weight and the minimum cost incurred, the patient needs to control the amount of food intake is by regulating the composition of food that enters the body. Patients need to control the amount of food intake to get the ideal body weight and the minimum expenditure is by regulating the composition of food that enters the body. The research was done by optimizing food composition for obese people in adults using Particle Swarm Optimization Algorithm (PSO). In this study, initial particle formation was carried out randomly based on the amount of food available so that it did not need to be changed into the food index. The results displayed by the program is actual body weight, ideal weight, nutritional status, energy needs, the needs of protein, fat and carbohydrate needs needs. While the test results obtained the optimal parameters such as the number of particles = 80, the number of iterations based on testing convergence of 703,
| Item Type: | Thesis (Sarjana) |
|---|---|
| Identification Number: | SKR/FTIK/2018/787/051809335 |
| Uncontrolled Keywords: | Algoritme Particle Swarm Optimization (PSO), Obesitas, Dewasa, Komposisi Makanan. Particle Swarm Optimization Algorithm (PSO), Obesity, Adult, Food Composition. |
| Subjects: | 000 Computer science, information and general works > 006 Special computer methods > 006.3 Artificial intelligence |
| Divisions: | Fakultas Ilmu Komputer > Teknik Informatika |
| Depositing User: | Budi Wahyono Wahyono |
| Date Deposited: | 15 Nov 2018 06:45 |
| Last Modified: | 22 Oct 2021 05:02 |
| URI: | http://repository.ub.ac.id/id/eprint/13800 |
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