Analisis dalam Melihat Perkembangan Indeks Harga Perdagangan Besar Menurut Sektor di Indonesia Menggunakan Algoritma Backpropagation
Zulfikar Zulfikar, Anjar Wanto, Zulaini Masruro Nasution · Prosiding Seminar Nasional Riset Information Science (SENARIS) · 2019
The Large Trade Price Index (IHPB) is one of the economic indicators that contains index numbers and shows changes in the price of goods purchased by traders from consumers. This study uses Artificial Neural Networks (ANN) with the Backpropagation method. Artificial neural networks are branches of artificial intelligence that mimic or imitate the workings of the human brain. The data of this study are secondary data sourced from the Central Statistics Agency (BPS) from 2000 to 2017. The data is divided into 2 parts, namely training data and testing data. There are 5 architectural models used in this study. 8-15-1, 8-25-1, 8-26-1, 8-30-1 and 8-40-1. From the 5 architectural models used 1 best model was obtained, namely 8-25-1 with an accuracy rate of 85%, MSE 0.00100074 and 10000 iterations. So this model is good for predicting large trade price indexes according to sectors in Indonesia in the future.