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All Journal JOMLAI: Journal of Machine Learning and Artificial Intelligence
Sari Marito Tondang
STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
Computer Science & IT Engineering

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Application of Artificial Neural Networks in Predicting Salt Imports by Country of Origin Using the Back-propagation Method Sari Marito Tondang; Heru Satria Tambunan; Susiani Susiani
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 3 (2022): September
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (401.659 KB) | DOI: 10.55123/jomlai.v1i3.919

Abstract

Salt is a basic consumption material needed by the community and various industries. Indonesia is a country that has many beaches that have great potential as a source of salt production. But Indonesia is still dependent on imports so that industrial imports continue to increase, can directly or indirectly affect the risk of the country’s economic pattern. An increase in salt imports although there was also a decrease but only slightly and did not last long from several countries from 2010-2020 recorded in the Central Statistics Agency (BPS). In this study, the author will predict the import of salt for the next 3 years using the Back-propagation algorithm. Back-propagation is one of the artificial neural network methods that is quite reliable in solving problems where the network tries to achieve stability again to achieve the expected output and there is a learning process by adjusting connection weights. This study uses 6 architectural models : 5-80-1, 5-90-1, 5-100-1, 5-110-1, from the four models the best architectural model is obtained namely 5-90-1 with an accuracy value of 75%, epoch 4265 iterations, and MSE Testing 0,01569.
Co-Authors Heru Satria Tambunan Susiani Susiani