Peramalan Menggunakan Metode Backpropagation Neural Network

Abstract

The purpose of the study is to forecast the price of rice in the city of Denpasar in 2017 using backpropagation neural network method. Backpropagation neural network is a model of artificial neural network by finding the optimal weight value. Artificial neural networks are information processing systems that have certain performance characteristics similar to that of human neural networks. This analysis uses time series data of rice prices in the city of Denpasar from January 2001 until December 2016. The results of this research, concludes that the lowest rice price is predicted in July 2017 at Rp9791.5 while the highest rice price in April 2017 for Rp9839.4.

Prediction of Salinity Based on Meteorological Data Using the Backpropagation Neural Network Method

“…The backpropagation method is also the most popular method to solve complex pattern recognition problems. In pattern recognition, this method consists of two phases, that is the forward propagation phase and the backward propagation phase (Sawitri et al, 2018). The network of the backpropagation method is included in a multilayer network where the network is composed of neurons that are connected at each layer, namely the input layer, hidden layer, and output layer as shown in Figure 2, there is which is the weight of the input layer to the hidden layer and there is a bias weight with a value of 1.…”

“…The backpropagation neural network method is the most popular method in data pattern recognition, prediction, and forecasting. A previous research which predicted the water distribution of PDAM in Malang City had an accuracy rate of 97.99% (Sawitri et al, 2018). A subsequent research, that is the prediction of rainfall in Pekanbaru City using the backpropagation method resulted in an accuracy of 96% (Jauhari et al, 2016).…”

Predicting The Number of Passengers on CV. MAKMUR Using The Backpropagation Method

“…The Backpropagation Neural Network Method is an excellent method for the pattern recognition process considering its ability to adapt network conditions to the data provided by the learning process [13]. The Backpropagation Neural Network Method is an excellent method for the pattern recognition process considering its ability to adapt network conditions to the data provided by the learning process [14]. Backpropagation is where the Backpropagation model has a hidden layer between input and output [15].…”

Prediksi Tingkat Kedatangan Wisatawan Asing Menggunakan Metode Backpropagation (Studi Kasus: Kepulauan Mentawai)

“…Peneliti lain yang memanfaatkan Jaringan Syaraf Tiruan Backpropagation, untuk peramalan harga beras berdasarkan hasil validasi diperoleh arsitektur jaringan terbaik untuk meramalkan harga beras di periode berikutnya adalah jaringan dengan fungsi aktivasi sigmoid biner yang terdiri dari satu unit input, tiga unit neuron lapisan tersembunyi dan satu unit lapisan output dengan nilai MSE sebesar 0,013472 [5]. Dan masih banyak lagi penelitian lainnya yang menerapkan algoritma Backpropagation dengan hasil lebih baik [10][11] [12].…”