Perfecting a Video Game with Game Metrics
Vol 17, No 1: February 2019

Integrating fuzzy logic and genetic algorithm for upwelling prediction in Maninjau Lake

Muhammad Rofiq (STMIK Asia Malang)
Yogie Susdyastama Putra (STMIK Asia Malang)
Wayan Firdaus Mahmudy (Universitas Brawijaya)
Herman Tolle (Universitas Brawijaya)
Ida Wahyuni (STMIK Asia Malang)
Philip Faster Eka Adipraja (STMIK Asia Malang)
Hafrijal Syandri (Universitas Bung Hatta)



Article Info

Publish Date
01 Feb 2019

Abstract

Upwelling is a natural phenomenon related with the increase in water mass that also occurs in Maninjau Lake, West Sumatra. The upwelling phenomenon resulted in considerable losses for freshwater fish farming because make mass mortalities of fish in farming using the method of floating net cages (karamba jaring apung/KJA). It takes a system that can predict the possibility of upwelling as an early warning to the community, especially fish farming to immediately prepare early anticipation of upwelling prevention. With historical water quality monitoring data at six sites in Maninjau Lake for 17 years, a prediction model can be made. There are three input criteria for Tsukamoto FIS that is water temperature, pH, and dissolve oxygen (DO). The model is built with fuzzy logic integration with the genetic algorithm to optimize the membership function boundaries of input and output criteria. After the optimization, hybrid Tsukamoto FIS and genetic algorithm successfully make a correct upwelling prediction on of 16 data with 94% accuracy.

Copyrights © 2019






Journal Info

Abbrev

TELKOMNIKA

Publisher

Subject

Computer Science & IT

Description

Submitted papers are evaluated by anonymous referees by single blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully in 10 weeks. Please notice that because of the great number of ...