CD Skripsi

Prediksi Harga Emas Dengan Metode Long Short-Term Memory

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Predicting gold prices holds significant importance in the realms of finance and investment, enabling market participants to make wiser decisions amidst gold price fluctuations. The training results of the Long Short-Term Memory (LSTM) model displayed remarkable performance, with a Mean Squared Error (MSE) value of 0.0034 and a Mean Absolute Percentage Error (MAPE) value of 7.13%. According to the MAPE criterion, this LSTM model's predictive capabilities can be categorized as highly accurate. These outcomes affirm the potential of the LSTM model in providing precise gold price predictions, aiding market participants in more informed decision-making. The forecasted gold prices using LSTM from January 1, 2023, to March 1, 2023, indicate a daily decrease in gold prices. Consequently, a prudent approach for market participants would be to engage in future gold purchases during the predicted gold price decrease in 2023.

Keywords: Data Scaling, Gold Price Prediction, LSTM, MAPE, MSE

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

1903156261

Penerbit

Pekanbaru : Universitas Riau – FMIPA – Sistem Informasi., 2023

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

1903156261

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

SISTEM INFORMASI

Info Detail Spesifik

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Pernyataan Tanggungjawab

Mutia

Versi lain/terkait

Lampiran Berkas

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