Prediksi Volume Penggunaan Air PDAM Menggunakan Metode Jaringan Syaraf Tiruan Backpropagation

  • Budy Satria AMIK Mitra Gama
Keywords: Backpropagation, Artificial Intelligence, Prediction, PDAM, Neural Network.

Abstract

As the population growth rate in Duri increases, the need for clean water also increases as needed. In Indonesia, PDAM is an institution that regulates and manages the provision of clean water for the community. So the amount of water produced and distributed should be adjusted to the demand for water. However, the problem arises in the form of waste of water at PT. PDAM Duri. Purpose of this study is to predict the amount of water consumption at PT. PDAM Duri by implementing Backpropagation  Artificial Neural Network method. Variables of data taken from customer data were social, general social, household 1, household 2, household 3, commerce 1, commerce 2 and commerce 3. Data used in the prediction process was training data in 2016 and data testing in 2017. Actual amount of data at PT. PDAM Duri City 2016 until 2017 was 2.840.165 when the prediction result using artificial neural network back propagation method was 2.843.388. The number of training epochs was 4595 and the achievement of MSE (Mean Squared Error) on the test was 0,001 and the result of accuracy was 99,99900000%. Final result of this research was artificial neural network using back propagation method could predict the using of water consumption at PT. PDAM  Duri for next year.

 

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Published
2018-10-17
Section
Technology Information Article