%0 Generic
%A Tri Novriyanda, Agung
%C UNIVERSITAS LAMPUNG
%D 2023
%F eprints:70820
%I FAKULTAS PERTANIAN
%T PREDIKSI MINYAK PADA LIMBAH CAIR KELAPA SAWIT  MENGGUNAKAN METODE MULTISENSOR 
%U http://digilib.unila.ac.id/70820/
%X    Predicting the oil content in palm oil liquid waste using the multisensor method is  one way to measure the oil content in palm oil liquid waste more quickly and  efficiently and get an accurate output value. This research aims to predict the oil  content in palm oil wastewater more quickly and efficiently and to obtain accurate  values using the multisensor method.    This research was conducted from June 2022 to January 2023. Waste sampling  was carried out at PTPN VII Bekri Lampung. Laboratory analysis was carried  out at the Basic Physics Laboratory, Department of Agricultural Engineering,  Faculty of Agriculture, University of Lampung. This study used an Artificial  Neural Network (ANN) with two hidden layers, learning rate 0.001, type of  training tranlm and number of epochs 1000. The training process of the artificial  neural network used 27 functional variations of logsig, tantig, and purelin  variants. The model validation process uses some of the data that has been  obtained during laboratory analysis.    The results of this study indicate model validation using 5 inputs, namely  electronic conductivity (EC), temperature, dissolved oxygen (DO), turbidity and  power of hydrogen (pH) input. RMSE value of 28.27 mg/l and RRMSE of 10.32 %    Keywords: Artificial Neural Networks, Oil, Palm Oil Wastewater.    ABSTRAK       Prediksi kadar minyak pada limbah cair kelapa sawit menggunakan metode   multisensor adalah salah satu cara untuk mengukur kadar minyak pada limbah  cair kelapa sawit secara lebih cepat dan efisien serta mendapatkan keluaran nilai  yang akurat. Pelitian ini bertujuan untuk Memprediksi kadar minyak pada limbah  cair kelapa sawit secara lebih cepat dan efisien serta mendapatkan nilai yang  akurat dengan metode multisensor.    Penelitian ini dilaksanakan pada bulan juni 2022 sampai januari 2023.  Pengambilan sampel limbah dilakukan di  PTPN VII Bekri Lampung. Analisis  laboratorium dilakukan di Laboratorium Fisika Dasar, Jurusan Teknik Pertaniaan,  Fakultas Pertanian, Universitas Lampung. Penelitian ini menggunakan Jaringan  Syaraf Tiruan ( JST)  dengan dua hidden layer, learning rate 0,001, tipe pelatihan  tranlm dan jumlah epoch 1000. Proses pelatihan jaringan syaraf tiruan  menggunakan 27 variasi fungsi dari varian logsig, tansig, dn purelin.     Hasil penelitian ini menunjukkan Validasi model dengan menggunakan 5 input  yaitu input electronical conductivity (EC), suhu, dissolved oxygen (DO), turbidity  dan power of hydrogen (pH). Nilai RMSE 28,27 mg/l dan RRMSE 10,32  %.     Kata Kunci : Jaringan Syaraf Tiruan, Minyak, Limbah cair kelapa sawit