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Abstract

Ministry of Marine Affairs and Fisheries (KKP) noted that Indonesia produced 56,539 tons of gourami fish in the second quarter of 2022 High market demand and economical selling prices encourage farmers to cultivate gourami fish. In cultivating gourami fish there are several obstacles, for example, disease caused by poor water quality. Water quality is the main parameter in the success of gourami fish farming. This research aims to develop a water quality monitoring system based on the Internet of Things. The system prototype uses a temperature sensor (DS18B20), Ph sensor (dfrobot SEN0161), turbidity sensor (dfrobot SEN0189), flowmeter, and ultrasonic sensor (JSN-SR04) as input. The Arduino Mega R3 microcontroller is the processor and the Oled module (SSD1306) is the output. Thingboard is a cloud server that functions as sensor data monitoring. Temperature sensor testing results (DS18B20) average error 0.48%, Ph(dfrobot SEN0161) sensor testing average error 0.64%, ultrasonic sensor testing (JSN-SR04) average error 7.83%, testing Turbidity sensors can measure the level of water turbidity. Next, the water quality parameter data is processed using the Naïve Bayes algorithm method for classifying the water quality of gourami ponds. The results of this classification obtained an accuracy of 99.94% a Kappa Statistics value of 0.9989 and a Mean Absolute Error of 0.0003

Keywords

Internet of Things Naïve Bayes Monitoring Classification

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