Open AccessPenerapan Algoritma Backpropagation dalam Memprediksi Persentase Penduduk Buta Huruf di Indonesia
Author(s) -
Imelda Asih Rohani Simbolon,
Fikri Yatussa’ada,
Anjar Wanto
Publication year - 2019
Publication title -
jurnal informatika upgris
Language(s) - English
Resource type - Journals
eISSN - 2477-6645
pISSN - 2460-4801
DOI - 10.26877/jiu.v4i2.2423
Subject(s) - functional illiteracy , backpropagation , indonesian , statistics , indonesian government , artificial neural network , mathematics , computer science , artificial intelligence , political science , linguistics , philosophy , law
Illiteracy is one of the most serious issues in Indonesia. The government's ignorance of illiterate people makes the illiteracy rate quite high. It should be one of the government's targets for reducing illiteracy in order to reduce the number of illiterate people. Illiteracy rate in Indonesia itself has reached 34.55% in Papua province. One way to suppress illiteracy rate in Indonesia is by predicting illiterate figures for subsequent years. The data to be predicted is the data of illiterate figures of each province in Indonesia which is sourced from the Indonesian Central Bureau of Statistics from 2011 to 2017. The method used in the prediction is Backpropagation Neural Network. Data analysis was done with the help of matlab software R2011b (7.13). This study uses 5 architectures, 4-5-1, 4-6-1, 4-9-1, 4-14-1 and 4-18-1. From these 5 models the best network architecture is 4-14-1 with 91% accuracy and Mean Squared Error 0,00274166.