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Roni Saputra, Roni
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Journal : Intechno Journal : Information Technology Journal

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The Effectiveness of Dropout Layers in LSTM Architecture for Reducing Overfitting in Sony Stock Prediction Saputra, Roni; Kurnia, Dian Ade; Wijaya, Yudhistira Arie
Intechno Journal : Information Technology Journal Vol. 7 No. 2 (2025): December
Publisher : Universitas Amikom Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24076/intechnojournal.2025v7i2.2369

Abstract

This study investigates the effectiveness of dropout layers in reducing overfitting within Long Short-Term Memory (LSTM) neural networks for Sony stock price prediction. Financial time series forecasting presents significant challenges due to market volatility and noise, often leading to models that overfit historical data while failing to generalize to unseen market conditions. We implemented two LSTM models: one without dropout layers and another with dropout layers (rate=0.2) applied after each LSTM layer. Using historical Sony stock data from 2015-2025, we evaluated both models using Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) metrics. The model with dropout demonstrated superior performance on testing data, achieving RMSE of 0.5971, MAE of 0.4411, and MAPE of 2.1502%, compared to the model without dropout which obtained RMSE of 0.7124, MAE of 0.5636, and MAPE of 2.6684%. Furthermore, the dropout model exhibited significantly reduced overfitting, with smaller performance gaps between training and testing datasets across all metrics, particularly in MAPE where the difference approached zero (0.0509%). This research provides empirical evidence that dropout regularization effectively enhances LSTM model generalization for stock prediction, offering practical value for developing more reliable financial forecasting models. Future research could explore optimal dropout rates for different market conditions and investigate combinations of dropout with other regularization techniques.
Co-Authors . Zulfan Adelirandy, Okky Adhe Aryswan Ahmad Rizalul Arifin AHMADI Alni, Bayu Rizky Andresta, Yulva Ardani, Novi Ardi, Ronal Ardimen Aulia, Risa Nur Bintang Wahyu Hakim Dana, Raditya dana Danov, Kamila Dewa, Barata Harsena DEWI FITRIANI Dewita, Trisna Dini Febriyenti Edinov, Sanny Fachrur Rozi Fadilah, Eka Fajrin, Aulia Febriani, Rindy Febrianita, Yulia Febrianto, Iwan Febriyenti, Dini Fitrima Sari, Siska Fyona, Annisa Gemala, Mega Ginting, Risa Astriani Haningrum, Katarina Silvia Hendri Neldi Herdianti Herdianti Herry Setiawan hilyatiaulia, Hanna Jamilus Jamilus Kamsyah, Domi Kurnia, Dian Ade Kurniawan, Yulius Lubis, Robi Hardi Ma'arif, Rohmatulloh Marlita, Lora Martanto . Maulana, Yoki Hasra Mistia Sari Murhenna Uzra Nasir, Janurdi Nugroho, Anan Nur Jading, Rasmin Nuraini, Aulia nurhayani, heni nurhayani Oktarizal, Hengky Pamungkas, Rifqi Nur Budi PARISMA, WAN INTAN Raditya Danar Dana Rahim, Radiyan Rahmayni, Wanda Ramadhani, Rizky Reffi Aryzegovina Rindiana, Ririn Eka Rita Dwi Pratiwi Rizandi, Hidayat Roni Ekha Putera S, Putri Wulandini Safitri, Khoerunnisa Said Sunardiyo Saputra, Ihsan Sari, Siska Fitrima Sasminta Christina Yuli Hartati Septifani Zalvia, Alya Siti Qomariah, Siti Solihudin, Dodi Sriyanto Sumantri, Ajis Suryani, Maysita Risma Tasya Yolanda, Refalina Tati Suprapti Tika Christy Utami, Isna Hayati Utami, Vanesa Uzma Septima Wendra, Yumai Wiwi Sartika Wulandini, Putri Wulandini, Putri Yamin, Moh Yasik, Muhammad Yudhistira Ardana, Yudhistira Yudhistira Arie Wijaya Yuliana, Liza Yunus, M Kailani Zahmi, April Zanuarta, Rozak Zulmuqim Zulmuqim, Zulmuqim