Analisis Pengaruh Earning Per Share, Harga Emas Dunia, Inflasi Terhadap Harga Saham Perusahaan Sektor Pertambangan Di Bursa Efek Indonesia Pada Masa Pandemi Covid-19

Fairuzie, Ahmad; Siagian, Arifin; Stefhani, Yosi

doi:10.54964/manajemen.v6i2.202

Cited by 2 publications

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“…Harga emas yang naik akan mendorong investor untuk memilih berinvestasi emas daripada di pasar modal karena memiliki risiko yang relatif lebih rendah. Hal ini disebabkan karena harga emas dapat memberikan hasil imbal balik yang baik dengan kenaikan harganya (Fairuzie et al, 2022). Oleh karena itu emas menjadi salah satu alat investasi yang banyak diminati oleh masyarakat.…”

Section: Pendahuluanunclassified

Aplikasi Model ARIMA dalam Peramalan Data Harga Emas Dunia Tahun 2010-2022

Rizki¹

2023

JSA

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Gold investment is one of the favorite investments during the Covid-19 pandemic because the price of gold is relatively volatile but shows an increasing trend. Savvy investors investing in gold need to be able to predict future opportunities. Therefore, price estimation is needed to develop a buying and selling strategy to maximize profits. The Autoregressive Integrated Moving Average (ARIMA) model is a suitable method for predicting time series data, so the best ARIMA model will be applied for forecasting world gold prices. The best ARIMA model is selected based on the Akaike Information Criterion (AIC) and Mean Absolute Percentage Error (MAPE) criteria. Monthly world gold price data for 146 periods are applied in this study and will be used to predict gold prices for the following six periods. ARIMA(0,1,1) is the best model obtained from the analysis results, with AIC and MAPE values of 1264.731 and 11.972%, respectively. Forecasting results show that world gold prices will increase for the next periods.

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Section: Pendahuluanunclassified

Aplikasi Model ARIMA dalam Peramalan Data Harga Emas Dunia Tahun 2010-2022

Rizki¹

2023

JSA

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Implementation of Long Short-Term Memory for Gold Prices Forecasting

Nurhambali,

Angraini,

Fitrianto

2024

MJMS

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Gold is a form of investment known as a safe haven asset because of its stability in unstable market conditions. Gold price forecasting is important for investors as decisions making tool. This study aims to study the best long short--term memory (LSTM) hyperparameters (optimizer, learning rate, and epoch) from cross--validation for forecasting. LSTM, as part of deep learning methods, is developed based on a RNN widely used in time series forecasting. LSTM is superior compared to other methods for its ability to minimize errors and forecast for long--term periods. Walk--forward validation with sliding and extending window scenarios as a form of cross--validation is used to see the method's accuracy. The used data is sourced from the World Gold Council with daily data periods for January 1, 2003, to December 31, 2023. The optimizer used is Adam and RMSProp, each with learning rate values of 0.01, 0.001, 0.0001, and epoch values of 100, 500, 1000. The best model uses the Adam optimizer, a learning rate of 0.01, and an epoch value of 100 with a MAPE value of 0.4867\% in the validation process. Forecasting results show a tendency for gold prices to increase in the next eight years.

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Analisis Pengaruh Earning Per Share, Harga Emas Dunia, Inflasi Terhadap Harga Saham Perusahaan Sektor Pertambangan Di Bursa Efek Indonesia Pada Masa Pandemi Covid-19

Cited by 2 publications

References 1 publication

Aplikasi Model ARIMA dalam Peramalan Data Harga Emas Dunia Tahun 2010-2022

Aplikasi Model ARIMA dalam Peramalan Data Harga Emas Dunia Tahun 2010-2022

Implementation of Long Short-Term Memory for Gold Prices Forecasting

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