Implementasi Regresi Linear dan Single Exponential Smoothing Dalam Prediksi Harga Saham ANTM

This study focuses on using linear regression and single exponential smoothing (SES) models to predict the share price of PT Aneka Tambang Tbk (ANTM). Data from Yahoo! Finance covering the period from 2005 to 2023 is used. The linear regression model establishes a relationship between the current and previous stock prices, while the SES model smoothes out fluctuations and captures shortterm trends. The findings reveal that both models are highly accurate in predicting ANTM stock prices. However, the SES model is less consistent in capturing shortterm trends, suggesting its effectiveness lies in capturing seasonal and short-term trends in the ANTM stock price data. This research is significant as it contributes to the development of accurate and reliable stock price prediction models, which can assist investors and players in the capital market in making informed investment decisions. The results also provide a foundation for future research on applying more complex and sophisticated forecasting models for stock price prediction.

Authors

Publication Details

Journal
TEKNOKOM
Published
2024-09-21
DOI
https://doi.org/10.31943/teknokom.v7i2.222
Primary Topic
Computer Science and Engineering
Type
article
Field-Weighted Citation Impact
0.00
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article

Implementasi Regresi Linear dan Single Exponential Smoothing Dalam Prediksi Harga Saham ANTM

Tundo Tundo, Rasiban Rasiban, Imam Paidi, Untung Suropati
TEKNOKOM
Computer Science and Engineering
article

Implementasi Regresi Linear dan Single Exponential Smoothing Dalam Prediksi Harga Saham ANTM

Tundo Tundo, Rasiban Rasiban, Imam Paidi, Untung Suropati
article en

Abstract

This study focuses on using linear regression and single exponential smoothing (SES) models to predict the share price of PT Aneka Tambang Tbk (ANTM). Data from Yahoo! Finance covering the period from 2005 to 2023 is used. The linear regression model establishes a relationship between the current and previous stock prices, while the SES model smoothes out fluctuations and captures shortterm trends. The findings reveal that both models are highly accurate in predicting ANTM stock prices. However, the SES model is less consistent in capturing shortterm trends, suggesting its effectiveness lies in capturing seasonal and short-term trends in the ANTM stock price data. This research is significant as it contributes to the development of accurate and reliable stock price prediction models, which can assist investors and players in the capital market in making informed investment decisions. The results also provide a foundation for future research on applying more complex and sophisticated forecasting models for stock price prediction.

TEKNOKOMVol. 7(2)
Openalex Percentile: Top 75%
Computer Science and Engineering
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Implementasi Regresi Linear dan Single Exponential Smoothing Dalam Prediksi Harga Saham ANTM — Tundo Tundo, Rasiban Rasiban, et al. · TEKNOKOM (2024) | TGRS Research Map | TGRS