Penerapan Teknik Neural Network dalam memprediksi Perkembangan Impor Kelompok Industri Tekstil dengan Metode Backpropagation

Ranjani, Suci Cahya Mita, Agus Perdana Windarto
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引用次数: 1

Abstract

The aim of this research is to analyze the development of the textile industry group in Indonesia using Artificial Intelligence. The analysis is conducted through a predictive model that will be used to predict the import development of the textile industry group. The dataset is sourced from the Indonesian Central Bureau of Statistics through the website https://www.bps.go.id/. The technique used is neural network with backpropagation method, and the analysis is conducted using Matlab. Backpropagation is a training method that has a target to be sought. This method is also a multilayer method, which has input, hidden, and output layers. The research process consists of two stages, namely the training stage and the testing stage. Out of several architecture models tested (3-10-1, 3-25-1, 3-50-1, 3-80-1, and 3-100-1), the best architecture model obtained is 3-100-1 with an MSE of 0.000999996 and an accuracy value of 100 percent.
通过反宣传方法预测纺织业集团的进口发展
本研究的目的是利用人工智能分析印尼纺织产业群的发展。通过预测模型进行分析,该模型将用于预测纺织工业集团的进口发展。该数据集通过https://www.bps.go.id/网站从印度尼西亚中央统计局获得。所采用的技术是神经网络反向传播方法,并利用Matlab进行了分析。反向传播是一种有目标的训练方法。这个方法也是一个多层方法,它有输入层、隐藏层和输出层。研究过程包括两个阶段,即训练阶段和测试阶段。在测试的几个体系结构模型(3-10-1、3-25-1、3-501、3-80-1和3-100-1)中,获得的最佳体系结构模型是3-100-1,MSE为0.000999996,精度值为100%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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