Penerapan Fuzzy Inference System untuk Sistem Pemantauan Kualitas Air pada Budidaya Cheerax Quadricarinatus
DOI:
https://doi.org/10.32493/informatika.v8i1.29214Keywords:
Redclaw, Kesesuaian Habitat, SAMOS, WSN, IoTAbstract
Cheerax quadricarinatus (Redclaw) becomes a fishery commodity that has high selling value with various advantages in terms of cultivation. In the Redclaw cultivation process, water quality is one of the indicators that require attention. Flawed water quality affects the conditions when the lobsters molt. In addition, shoddy water quality also impacts the slow growth rate and high mortality during ontogeny. The level of water quality is influenced by the parameters of Temperature, Potential of Hydrogen (pH), Ammonia, and Total Dissolved Solid (TDS). The level of water quality requires monitoring in real-time with the aim of being able to find out the latest conditions according to the category of aquaculture pond. Water quality monitoring is carried out by implementing a Fuzzy Inference System in a Water Quality Monitoring System based on a Wireless Sensor Network (WSN) and the Internet of Things (IoT). The water quality monitoring system is running well, marked by all sensors being able to send parameter values and the monitoring dashboard being able to display all parameter values along with water quality and condition values. The water quality level results show that the pond's cultivation habitat is in a suitable category, indicated by a water quality value of more than 90%. The level of water quality can be represented as suitability for Redclaw habitat to increase growth.References
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