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All Journal Computer Science (CO-SCIENCE)
Frandy Ristianto
Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri
Computer Science & IT

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Impementasi Metode Naive Bayes Untuk Prediksi Harga Emas Frandy Ristianto; Nurmalasari Nurmalasari; Ani Yoraeni
Computer Science (CO-SCIENCE) Vol. 1 No. 1 (2021): Januari 2021
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v1i1.201

Abstract

Gold is a profitable asset to invest in. With a risk that is not too big. However, many factors influence the price, one of which is the fluctuation of the exchange rate (IDR) rupiah against the USD currency (US Dollar). Data Mining is used to predict the price of gold, with the process of extracting past data, the data used is from the www.bps.go.id data to add added value in the form of information that has not been known manually from a database in order to see patterns and can predict the price of gold. One of the data mining methods used is Naïve Bayes and uses Rapid Miner software as a process to assist calculations with the data set used for 3 years, namely from January 2016 - December 2019 and prediction of data training for the next 1 year assuming stable prices, with testers as much as 5 times 52 data, where in the application of opportunities based on the history of events that occurred so that the accuracy is good at 95.92% to apply and see profit opportunities whether or not the gold price
Co-Authors Nurmalasari Nurmalasari Yoraeni, Ani