Abstract
Water quality management is very important to do, because water is an inseparable part of everyday human life. Monitoring water quality is a way to maintain the quality of waters, especially rivers. River quality monitoring that is usually done requires a lot of equipment, effort and expertise so that its application becomes expensive and complicated. Technology that is growing rapidly nowadays puts forward artificial intelligence as the backbone of the Industrial Revolution 4.0 which promises many conveniences for industry and government. One of artificial intelligence technology is machine learning with Artificial Neural Network algorithm which is commonly used to predict or forecast a future value. This artificial neural network can be used to help monitor river water quality. The objective of this research to develop Artificial Neural Networks (ANN) model to predict the paramater of river quality (DO, pH, turbidity, temperature, water flow, conductivity) in the Subayang River, Kampar Regency, using software Rapidminer. The performance of the ANN models was evaluated using root mean squared error (RMSE) and correlation squared (R2) as a second comparison, then the results of the testing implementation are compared with direct measurements in the field. With the RMSE values obtained in the test results of each parameter DO = 1.613, pH = 0.098, turbidity = 4.730, temperature = 0.493, water flow = 0.121 and conductivity = 0.909. The lower the RMSE level, the closer it is to Artificial Neural Network accuracy for value prediction.
Highlights
because water is an inseparable part of everyday human life
a way to maintain the quality of waters
River quality monitoring that is usually done requires a lot of equipment
Summary
Penelitian ini akan dilakukan di Sungai Subayang, Kecamatan Kampar Kiri Hulu Kabupaten Kampar Riau, pada bulan Maret 2019 hingga April 2019. Gambar 1 menunjukkan lokasi titik pantau dilakukan di tiga stasiun monitoring kualitas air WWF Indonesia, pada hulu sungai di Desa Aur Kuning, tengah Sungai di Desa Batu Sanggan dan hilir sungai di Desa Tanjung Belit. Pendekatan pada penelitian ini menggunakan deskriftif kuantitatif dan dengan metode survei (Yusuf, 2017) peneliti menggambarkan bagaimana dengan menerapkan kecerdasan buatan menggunakan algoritma Artificial Neural Network dapat memprediksi kualitas perairan Sungai Subayang menggunakan data historikal kualitas air selama tiga tahun, sehingga diketahui kondisi terkini perairannya. Hasil prediksi tersebut divalidasi keakuratannya dengan metode perhitungan kesalahan yaitu RMSE (roort mean square) dan R2 (R-squared)
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