PREDIKSI PEMAKAIAN AIR MENGGUNAKAN METODE BACKPROPAGATION (STUDI KASUS PDAM TIRTA WAMPU)

Nuri Afrida; Suci Ramadani; Indah Ambarita

Nuri Afrida * STMIK Kaputama Binjai, Binjai, Indonesia
Suci Ramadani STMIK Kaputama Binjai, Binjai, Indonesia
Indah Ambarita STMIK Kaputama Binjai, Binjai, Indonesia

(*) Corresponding Author

Keywords: Prediction; Water Usage; Artificial Neural Network; Backpropagation

Abstract

Water is one of the necessities and a source of life that is very vital and absolutely necessary for all living things, especially humans. That's why the supply of clean water is very necessary for consumption purposes, high water use results in the need for clean water availability continues to increase, while the supply of clean water continues to decrease every year along with the large number of open green lands that are used as settlements or buildings. For this reason, PDAM needs to provide as much water as possible so that it can meet daily human needs. The Backpropagation method is one of the methods in Artificial Neural Network which has one or more hidden layers and a back propagation process for error correction. Based on the analysis that has been carried out, namely from training data, training targets and water usage test data, it can produce predictions on the number of predictions for the amount of water use with a total prediction of 43633298 M3 which has increased in the previous year, namely 4362905 M3, with a target error of 0.2, the length of iteration with a duration of time. or the length of learning is 00.17.

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