Komparasi Algoritma Machine Learning Dalam Identifikasi Kualitas Air

Abstract

Water is the most important part of human life because it is the source of human life and about 71% of the earth's area is water. Every human being has the human right to clean water which is a basis for the realization of a decent and dignified life for humans. Classification is one of the techniques in data mining. This study uses water quality data using four algorithmic methods, namely Decission Tree, Logistic Regression, SVM, and ANN. The aim of this research is to compare which method has the maximum accuracy value for water quality classification. The accuracy results obtained are the Decission Tree method of 60.19%, the Logistic Regression method of 62.80%, the SVM method of 68.59%, and the ANN method of 69.54%.