OPTIMASI DERAJAT KEANGGOTAAN FUZZY TSUKAMOTO MENGGUNAKAN GENETIC ALGORITHM UNTUK MENENTUKAN KECUKUPAN GIZI PADA POLA MAKANAN BALITA

PARAMITHA, PINAKESTI and Utami, Alvi Syahrini and Miraswan, Kanda Januar (2021) OPTIMASI DERAJAT KEANGGOTAAN FUZZY TSUKAMOTO MENGGUNAKAN GENETIC ALGORITHM UNTUK MENENTUKAN KECUKUPAN GIZI PADA POLA MAKANAN BALITA. Undergraduate thesis, Sriwijaya University.

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Abstract

This study discusses the use of genetic algorithms to optimize the degree of membership in Fuzzy Tsukamoto in the case of determining the nutritional adequacy of the toddler's diet. Use of Fuzzy Tsukamoto will tolerate malnutrition so that the value is not decisive, while the use of genetic algorithms will optimize fuzzy membership degree range so that the resulting solution will be optimized. The performance of the Fuzzy Tsukamoto method whose membership degree is optimized by the genetic algorithm is by using the parameters mr = 0.3, cr = 0.7, population = 100, and iteration = 50. From the test it was found that the use of genetic algorithms reached 53.33% as the highest accuracy and 49.33% as the average accuracy. While the accuracy of the degree of membership without optimization is obtained by 40%.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Algoritma Genetika, Fuzzy Tsukamoto, Gizi pada Makanan Balita
Subjects: R Medicine > R Medicine (General) > R858-859.7 Computer applications to medicine. Medical informatics
T Technology > T Technology (General) > T1-995 Technology (General)
Divisions: 09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User: Pinakesti Paramitha
Date Deposited: 24 Aug 2021 07:28
Last Modified: 24 Aug 2021 07:28
URI: http://repository.unsri.ac.id/id/eprint/52637

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