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All Journal Dielektrika
KUSRINI
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Computer Science & IT Electrical & Electronics Engineering Energy

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Study Literature Study on Predicting Gold Prices using Machine Learning Sri Wahyuningsih; Kusrini; Hanafi
DIELEKTRIKA Vol 10 No 2 (2023): DIELEKTRIKA
Publisher : Jurusan Teknik Elektro Fakultas Teknik Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/dielektrika.v10i2.335

Abstract

Gold is a metal that is believed to be able maintain prices and can be a medium of exchange that has different forms and functions. In addition, gold can be used as a long-term investment tool at various prices. Price variations can be influenced by many factors, so predicting gold prices can minimize risk. Gold price predictions are not only interesting for collectors but also interesting for analysts to discuss. Machine learning is one method that is often used to predict gold prices. In this study will discuss the study of literature based on the methods and results of previous literature. The purpose of this study is to determine the best performance of the methods that have been used and can be used as a reference in predicting gold prices. The purpose of writing this journal is to provide an overview as well the benefits of applying data mining techniques to machine learning. These benefits include development better understanding of machine learning, as well as improved decision making and technological innovation.
Co-Authors Hanafi Sri Wahyuningsih