Author:
Pratiwi Heny,Windarto Agus Perdana,Susliansyah S.,Aria Ririn Restu,Susilowati Susi,Rahayu Luci Kanti,Fitriani Yuni,Merdekawati Agustiena,Rahadjeng Indra Riyana
Abstract
Abstract
The aim of the research is to make predictions from the best architectural model of backpropagation neural networks. In determining the outcome in the form of a prediction model, the activation function in the artificial neural network is useful to transform an input into a certain output. In this study the activation function used is sigmoid. The study uses the case of population density in Indonesia considering that for developing countries population growth has many negative impacts such as increased poverty, unemployment and crime rates. This study uses data from Badan Pusat Statistic Indonesia for population categories in 2003-2015. The process of determining the architectural model is carried out 2 stages including: the training stage and the testing stage. The two architectural models used (5-2-1 and 5-10-1), the selection of architectural models is done by looking at several assessment parameters such as epoch, accuracy, MSE training and MSE testing. The process of training and testing of data is done by using the help of the Matlab application. The results of the study obtained that the architectural model 5-2-1 is the best model for predicting with an accuracy of 65%, MSE Training 0,0009997254, MSE Testing 0.0014897214 and Epoch 28548.
Subject
General Physics and Astronomy
Reference12 articles.
1. Neural networks optimization through genetic algorithm searches: A review;Chiroma;Applied Mathematics and Information Sciences,2017
2. Use of Binary Sigmoid Function And Linear Identity In Artificial Neural Networks For Forecasting Population Density;Wanto;International Journal Of Information System & Technology,2017
3. Implementation of Artificial Intelligence in Predicting the Value of Indonesian Oil and Gas Exports With BP Algorithm;Windarto;International Journal of Recent Trends in Engineering & Research (IJRTER),2017
4. Analysis of Backpropagation Method with Sigmoid Bipolar and Linear Function in Prediction of Population Growth;Siregar;Journal of Physics: Conference Series,2019
5. Bipolar function in backpropagation algorithm in predicting Indonesia’s coal exports by major destination countries;Febriadi;IOP Conference Series: Materials Science and Engineering,2018
Cited by
43 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献