Gold Price Prediction Based on Gold.org Data Using the Long Short Term Memory Method

Prasetyo, Vincentius Riandaru and Axel, Stefan and Soebroto, Juan Timothy and Sugiarto, David and Winatan, Septian Ardi and Njudang, Senradel Daniel (2022) Gold Price Prediction Based on Gold.org Data Using the Long Short Term Memory Method. Jurnal SISTEMASI, 11 (3). pp. 623-629. ISSN 2540-9719

PDF Vincent_Artikel Jurnal Sistemasi_Vol 11_No 3.pdf - Published Version Download (1MB)

Abstract

Gold is one form of precious metal with priceless value in this day and age. Therefore, many people are starting to invest in gold. Someone who wants to invest in gold must pay attention to changes in gold's buying and selling price. One site that can be used as a reference to see changes in the price of buying and selling gold is gold.org. Several factors influence gold price changes, namely changes in the value of the US Dollar exchange rate, the amount of world gold production, and the increase in demand for gold itself. This means that the price of gold tends to be unstable because of frequent changes. The LSTM or Long Short Term Memory method can be implemented to predict gold prices based on previous gold prices. The prediction model built in this study predicts gold price in the future based on 60 last gold price data. Based on the results of accuracy measure, an accuracy of 87.84% was obtained with the value of the difference between the original price and the prediction of 5 and the number of epochs being 100.

Item Type:	Article
Uncontrolled Keywords:	prediksi, harga emas, LSTM
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Divisions:	Faculty of Engineering > Department of Informatic
Depositing User:	VINCENTIUS RIANDARU PRASETYO
Date Deposited:	04 Oct 2022 08:17
Last Modified:	04 Oct 2022 08:17
URI:	http://repository.ubaya.ac.id/id/eprint/42664

Actions (login required)

View Item