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BAHRUDI EFENDI DAMANIK
AMIK TUNAS BANGSA, PEMATANGSIANTAR, INDONESIA
Arts Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Economics, Econometrics & Finance Education Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Public Health Social Sciences Other

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THE ARTIFICIAL NEURAL NETWORK (ANN) ALGORITHM IMPLEMENTATION FOR PREDICTING THE AMOUNT OF BOOK SALES AT ERLANGGA PUBLISHER PEMATANGSIANTAR HOTMALINA SILITONGA; INDRA GUNAWAN; BAHRUDI EFENDI DAMANIK
INTERNATIONAL JOURNAL OF MULTI SCIENCE Vol. 1 No. 12 (2021): INTERNATIONAL JOURNAL OF MULTISCIENCE - MARCH 2021 EDITION
Publisher : CV KULTURA DIGITAL MEDIA

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Abstract

Selling is one of the main goals of a company after producing its goods. The more goods sold, the more economic value the company is selling. Therefore, the purpose of this study is to determine how much the rate of increase or decrease in the number of book sales at the publisher of Erlangga Pematangsiantar is in the form of prediction. This study uses an Artificial Neural Network (ANN) with the Backpropagation method. Backpropagation is a method that is often used for prediction. The research data is secondary data (sales data) sourced from PT. Publisher Erlangga Pematangsiantar from 2013 to 2017. Data is divided into 2 parts, namely training data and testing data. There are 5 architectural models used in this study, 3-9-1, 3-11-1, 3-15-1, 3-30-1, and 3-31-1. Of the 5 (five) architectural models used, the best architecture is 3-11-1 with an accuracy rate of 80% and MSE 0.13001601. So this model is good for predicting the number of book sales at PT. Publisher Erlangga Pematangsiantar.
Co-Authors HOTMALINA SILITONGA INDRA GUNAWAN