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

*Herryawan Pujiharsono orcid scopus  -  Institut Teknologi Telkom Purwokerto, Indonesia
Danny Kurnianto orcid  -  Institut Teknologi Telkom Purwokerto, Indonesia
Received: 17 Dec 2018; Revised: 6 Jan 2020; Accepted: 18 Jan 2020; Published: 30 Apr 2020; Available online: 5 Feb 2020.
Open Access Copyright (c) 2020 Jurnal Teknologi dan Sistem Komputer
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Section: Original Research Articles
Language: ID
Statistics: 485 160
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

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