Purwarupa Perahu untuk Monitoring dan Klasifikasi Kualitas Air Bendungan dengan Metode K-Nearest Neighbor (KNN)

Chikam Muhammad (Fakultas Ilmu Komputer, Universitas Brawijaya)
Rizal Maulana (Fakultas Ilmu Komputer, Universitas Brawijaya)
Mochammad Hannats Hanafi Ichsan (Fakultas Ilmu Komputer, Universitas Brawijaya)

Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Vol 4 No 2 (2020): Februari 2020

Water quality monitoring activities that most people do nowadays still using manual method and less effective. Rivers, dams, and reservoirs are objects that typically used for water quality monitoring activities. For dam monitoring activities, related parties need to manually monitor water quality at dams water inlet, midpoint and water outlet. because of this, a tool created for automatic water quality monitoring. A tool with five parameters, consisting of water depth sensor,turbidity sensor, water temperatur sensor, water pH sensor, and sensor TDS. The tool was created that can move to monitoring water. This research uses two microcontrollers for procesing purposes. Arduino nano for data acquisition while node MCU for k-NN classification method and sending five sensors data with the classification result to firebase. So it can displayed to user applications. The results of classification are three classes. Classes of “Good”, “Medium”, “Bad”. Amount of data used are 75 data, divided into 50 data for training data and then 25 data for test data. The result of k-NN classification test was 92% in accuracy with K = 5. And the computation time test was caried out ten times and the result system of 4135 ms.