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Qoirul Kotimah
Brawijaya University, Indonesia
Computer Science & IT Electrical & Electronics Engineering

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Optimization of Fuzzy Tsukamoto Membership Function using Genetic Algorithm to Determine the River Water Qoirul Kotimah; Wayan Firdaus Mahmudy; Vivi Nur Wijayaningrum
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (329.255 KB) | DOI: 10.11591/ijece.v7i5.pp2838-2846

Abstract

Some aquatic ecosystems in rivers depend on the river water, so it needs to be maintained by measuring and analyzing the river water quality. STORET is one of the methods used to measure the river water quality, but it takes a quite high of time and costs. Fuzzy Tsukamoto is an alternative method that works by grouping the river water data, but it is difficult to determine the membership function value. The solution offered in this study is the use of genetic algorithm to determine the membership function value of each criterion. Based on the test results, the optimization of fuzzy membership function using genetic algorithm provides higher accuracy value that is 95%, while the accuracy value without optimization process is 90%. The parameters used in genetic algorithm are as follows: population size is 80, generation number is 175, crossover rate (cr) is 0.6, and mutation rate (mr) is 0.4.
Co-Authors Vivi Nur Wijayaningrum Wayan Firdaus Mahmudy