Perbandingan Metode Artificial Neural Network dan Convolutional Neural Network untuk Memprediksi Jumlah Distribusi Air di PDAM Kota Denpasar
DOI:
https://doi.org/10.23887/jstundiksha.v12i2.47800Keywords:
Artificial Neural Network, Convolutional Neural Network, Distribusi Air, Sequential Forward SelectionAbstract
Kelangsungan hidup di dunia pasti tidak akan bisa terlepas dari penggunaan air. Seiring dengan berkembangnya zaman tentu akan diikuti dengan bertambahnya jumlah penduduk yang juga akan berdampak terhadap meningkatnya kebutuhan air bersih. PDAM merupakan salah satu instansi yang melayani ketersediaan air bersih. Tujuan diadakannya penelitian ini untuk melakukan peramalan terhadap jumlah distribusi air di PDAM Kota Denpasar dengan membandingkan metode ANN (Artificial Neural Network) serta CNN (Convolutional Neural Network) yang juga melibatkan proses seleksi fitur menggunakan metode SFS (Sequential Forward Selection). Pendekatan kuantitatif digunakan untuk melakukan proses peramalan terhadap jumlah distribusi air (Y) dengan melibatkan fitur jumlah produksi (X1), kebocoran (X2), pembelian (X3), dan pelanggan air (x4). Hasil seleksi fitur dengan metode SFS menujukkan bahwa jumlah produksi air (X1) dan kebocoran air (X2) dengan tingkat kesalahan sebesar 0.031069 tepat digunakan untuk membentuk model peramalan jumlah distribusi air dengan metode ANN yang menghasilkan nilai MSE dan MAPE berturut-turut sebesar 0.040 serta 2.02%. Berdasarkan hasil yang diperoleh, model yang dikembangkan termasuk model peramalan yang sangat baik, sehingga tepat digunakan untuk melakukan proses peramalan jumlah distribusi air.
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