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Jurnal Teknologi Informasi dan Terapan (J-TIT)
Published by Politeknik Negeri Jember
ISSN : 2354838X     EISSN : 25802291     DOI : https://doi.org/10.25047
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
This journal accepts articles in the fields of information technology and its applications, including machine learning, decision support systems, expert systems, data mining, embedded systems, computer networks and security, internet of things, artificial intelligence, ubiquitous computing, wireless sensor networks, and cloud computing. The journal is intended for academics and practitioners in the field of information technology.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 11 Documents
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Search results for , issue "Vol 11 No 2 (2024): December" : 11 Documents clear
IoT-Based Water Quality Monitoring System for Fish Ponds Using Fuzzy Inference Method Achmad Firman Choiri
Jurnal Teknologi Informasi dan Terapan Vol 11 No 2 (2024): December
Publisher : Jurusan Teknologi Informasi Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/jtit.v11i2.441

Abstract

This study uses the fuzzy inference method to develop an Internet of Things (IoT) system to monitor fish pond water quality. This system utilizes pH, Total Dissolved Solids (TDS), and temperature sensors to measure water quality parameters for fish health. Although many previous studies have discussed water quality monitoring, there are still limitations in applying IoT technology integrated with fuzzy inference methods for real-time data analysis. Many existing systems cannot provide information easily understood by fish farmers and are less accurate in measuring water quality parameters. Arduino Nano is the main microcontroller that processes sensor data, while the ESP8266 module is used for Wi-Fi connection for real-time monitoring through the thinger.io web-based application. Before testing, the sensors have been calibrated to ensure measurement accuracy. The test results on three water samples, namely tap water, tilapia pond water, and mujaer pond water, showed high accuracy and consistent results. The fuzzification results from the IoT device are close to the Simulink Fuzzy test results on each sample, with minor differences in tilapia pond water, likely caused by environmental factors such as aeration or sensor precision. This study aims to provide a system that is not only accurate but also presents data in a more understandable format so that it can help fish farmers make better pond management decisions. Thus, this study is expected to increase fish farming productivity through better and technology-based water quality management

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