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All Journal METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi
Gomgom Triputra Sinaga
Universitas Methodist Indonesia
Computer Science & IT Economics, Econometrics & Finance

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Prediksi Harga Saham Apple Inc (AAPL) Menggunakan Metode Single Exponential Smoothing Gomgom Triputra Sinaga; Jimmy Febrinus Naibaho; Jhoni Maslan
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 10 No. 1 (2026): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol10No1.pp373-379

Abstract

The stock price movement of Apple Inc. (AAPL) exhibits high levels of fluctuation and volatility, necessitating adaptive forecasting methods to assist investors in decision-making. This study aims to implement the Single Exponential Smoothing (SES) method to predict the closing price of AAPL stock based on historical data. The research methodology involves processing 1,256 daily data points from Investing.com for the period October 2020 to October 2025 using the Python programming language. The results indicate that using a smoothing parameter of $\alpha = 0.9$ yields the most optimal performance with a Mean Absolute Percentage Error (MAPE) of 1.29% and a Mean Absolute Error (MAE) of $2.2267. With a MAPE value below 10%, the accuracy of this model is classified as Highly Accurate. The system generates an estimated AAPL stock price for the next period of $258.87, proving that the SES method is effective for short-term forecasting on volatile data
Co-Authors Jhoni Maslan Jimmy Febrinus Naibaho