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Sistem inferensi fuzzy Mamdani untuk menentukan tingkat kualitas air pada kolam bioflok dalam budidaya ikan lele

Mamdani fuzzy inference system for mapping water quality level of biofloc ponds in catfish cultivation

Institut Teknologi Telkom Purwokerto, Indonesia

Received: 17 Dec 2018; Revised: 6 Jan 2020; Accepted: 18 Jan 2020; Available online: 5 Feb 2020; Published: 30 Apr 2020.
Open Access Copyright (c) 2020 Jurnal Teknologi dan Sistem Komputer
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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Abstract
The government has launched a program to increase the production of catfish by using biofloc ponds. The biofloc ponds can maintain the quality of water biologically to maximize the growth of fish. However, the level of water quality monitoring is generally only divided into good or bad categories so that it cannot represent the condition of fish growth. Therefore, this study aims to get the level of water quality (0–100 %) using the Mamdani fuzzy inference system (FIS) algorithm based on pH, temperature, and dissolved oxygen (DO). The level of water quality was correlated based on catfish growth conditions. The results showed that the range of values of the water quality level for each condition of catfish growth was 100 % for normal-living fish, 83–99 % for stunted fish growth, and < 83% for threatened fish. The FIS algorithm had 89.92 % of accuracy.
Keywords: Mamdani FIS; pH level; temperature monitoring; dissolved oxygen concentration; catfish biofloc
Funding: Kementerian Riset, Teknologi, dan Pendidikan Tinggi, Indonesia

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Last update: 2024-11-12 15:59:22

  1. Fountains Height Measurement Accuracy With Mamdani Fuzzy Inference System Algorithm

    Retno Devita, Ruri Hartika Zain, Ipriadi. Journal of Physics: Conference Series, 1783 (1), 2021. doi: 10.1088/1742-6596/1783/1/012009