Jaringan Saraf Tiruan untuk Memprediksi Jumlah Pasien Rawat Jalan bagi Pengguna Narkoba Menggunakan Metode Backpropagation

(Studi Kasus : Kantor BNN Kota Binjai)

  • Devy Armaya Lestari STMIK KAPUTAMA
  • Budi Serasi Ginting STMIK KAPUTAMA
  • Nurhayati Nurhayati STMIK KAPUTAMA
Keywords: JST, Backpropagation, outpatient, prediction

Abstract

The National Narcotics Agency of Binjai City has the duty and function of preventing the abuse of narcotics, eradicating illicit narcotics trafficking, and rehabilitation of narcotics addicts in Binjai City. The National Narcotics Agency is also tasked with compiling and implementing national policies regarding the prevention and eradication of the abuse and illicit trafficking of psychotropic substances, precursors and other addictive substances except for tobacco and alcohol addicts. So we need an application that can predict the number of outpatient visits. Based on the analysis process that has been carried out under the artificial neural network system using the Backpropagation method, it can be implemented into an artificial neural network application and produces predictions of outpatient drug users with an average of 93 patients inex users, 78 patients of marijuana and 92 patients with crystal meth result 0.302960 equals 30.

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Author Biographies

Budi Serasi Ginting, STMIK KAPUTAMA

Program Studi Teknik Informatika

Nurhayati Nurhayati, STMIK KAPUTAMA

Program Studi Teknik Informatika

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Badan Narkotika Nasional
Published
2020-10-11
Section
Articles