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All Journal IJESPG (International Journal of Engineering, Economic, Social Politic and Government) journal
Ade Kanianingsih
Program Studi Informatika, Fakultas Sains dan Informatika Universitas Jenderal Achmad Yani
Computer Science & IT Economics, Econometrics & Finance Engineering Law, Crime, Criminology & Criminal Justice Social Sciences

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Peramalan Indeks Harga Saham PT XYZ Menggunakan Metode Double Moving Average (DMA) M.Naufal Rafirhan; Ade Kanianingsih; Agus Komarudin
IJESPG (International Journal of Engineering, Economic, Social Politic and Government) Vol. 1 No. 3 (2023)
Publisher : IJESPG (International Journal of Engineering, Economic, Social Politic and Government)

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Abstract

The stock price index is an indicator that is useful as an illustration of the movement of stock prices in a period. Forecasting on the stock price index can be used as a reference or benchmark in capital market activities and products resulting from investment. In this study, there is a goal to be achieved, namely to predict the stock price index at PT XYZ based on existing historical data to see how accurate the forecast is made on actual data using the forecasting method, namely the Double Moving Average (DMA) method, which is a model. forecasting to determine the trend of a time series, so that it will obtain stock price index value forecasting data based on existing historical data. In this research, forecasting will be carried out regarding the stock price index for the period June 2018 - June 2023 at PT XYZ (Persero) Tbk, which is one of the BUMNs engaged in the construction sector. Based on the results obtained by forecasting the Double Moving Average (DMA), the values for forecasting the stock price index for the value for forecasting the stock price index for the Open index type is 3.27%, High 3.11%, Low 3.10%, and Close 3.17% each having a MAPE value of <10% . So that in the research "PT XYZ STOCK PRICE INDEX FORECASTING USING THE DOUBLE MOVING AVERAGE (DMA) METHOD" the performance of the prediction model carried out has very good and accurate performance.
Co-Authors Agus Komarudin M.Naufal Rafirhan