Implementasi Algoritme K-Nearest Neighbour pada Sistem Monitoring dan Klasifikasi Air Aquarium Ikan Koi berbasis Embedded System - Dwi Firmansyah; Dahnial Syauqy; Rizal Maulana (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2019)
Aquarium water conditions that are not good can cause disruption to fish health, water conditions that tend to be unstable can interfere and threaten the health of fish. Ammonia gas that is dissolved in water exceeds a threshold that can be tolerated by koi fish can cause koi fish tend to be inactive in the aquarium due to food debris or feces from the fish. The mq-135 sensor is a device for detecting unpleasant odors in the air, which in this system is used to obtain the value of ammonia gas contained in the water content. Salinity or dissolved salt levels in aquarium water can also cause irritation to fish skin and people so that fish tend to rub against the bottom of the aquarium, but if the salt level is well maintained it can prevent, treat and kill bacteria that interfere with fish health, one of which is a bacterium caused by fish waste (ammonia). So that in this study a system was made that could classify the condition of the aquarium water by implementing the k-nearest neighbor method. The input of this system is the reading value of the ammonia gas sensor and electrical conductivity which will then compute and display the classification results on the LCD and the sensor reading value sent to the thingspeak platform. The results of this study obtained an accuracy of 27.28% for testing the k value and testing the time needed to do the computation so as to obtain classification results with an average of 1897.5ms or 1.9 seconds.