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All Journal JSI: Jurnal Sistem Informasi (E-Journal) Journal of Educational Science and Technology Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Komputer Terapan Seminar Nasional Teknologi Informasi Komunikasi dan Industri INOVTEK Polbeng - Seri Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Dinamisia: Jurnal Pengabdian Kepada Masyarakat ILKOM Jurnal Ilmiah KAIBON ABHINAYA : JURNAL PENGABDIAN MASYARAKAT Jurnal Pengabdian Masyarakat Multidisiplin Literasi: Jurnal Pengabdian Masyarakat dan Inovasi Proceeding Applied Business and Engineering Conference JITER-PM (Jurnal Inovasi Terapan - Pengabdian Masyarakat) SATIN - Sains dan Teknologi Informasi Jurnal Informatika: Jurnal Pengembangan IT
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Developing an Educational Software Platform for Stock Learning Using LSTM Forecasting Models Nurmalasari, Dini; Alfani, Yessi; Yuliantoro, Heri R; Fitrisia, Yuli
Journal of Educational Science and Technology (EST) Volume 11 Number 3 December 2025
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/est.v11i3.81360

Abstract

This study aims to develop an educational software platform that supports Indonesian students in learning stock market behavior by addressing low financial literacy, limited analytical skills, and emotion-driven investment decisions. The proposed platform integrates historical data from liquid IDX80 stocks with a Long Short-Term Memory (LSTM) forecasting model enhanced by technical indicators and calendar-based market features, and presents predicted price movements and trend classifications through an interactive, user-friendly learning interface. Experimental results show that the model achieved strong predictive performance on most IDX80 stocks, demonstrating its ability to capture temporal price patterns, while the inclusion of technical and calendar-based features improved prediction clarity and trend interpretability for student users. Variations in forecasting accuracy across stocks indicate that liquidity and volatility influence model performance, highlighting the importance of contextual interpretation in learning. In conclusion, the findings indicate that integrating LSTM-based forecasting with instructional design principles can support experiential and data-driven investment learning, and the developed platform demonstrates strong potential as both a forecasting tool and an educational technology medium for supporting financial literacy development. 
Co-Authors Akbar, Memen Akbar, Memen Alfani, Yessi Alim Syahbana, Yoada Alim Syahbana, Yoanda Anggy Trisnadoli Ayu Putri Hanifah Debi Gustian Dewi Hajar Erwin Setyo Nugroho Fadhly, Mardhiah Fadli, Mardhiah Indah Lestari Jordan Abeth Teofilus Pasaribu Kartina Diah K. W. Kasna, Sinria Mardhiah Fadhli, Mardhiah Maruf Alfiando Setianto Muhammad Akbar Agung Triputra mutia sari zulvi Nurmalasari, Dini Owen, Marcel Purwantoro E.S.G.S, Sugeng Purwantoro, Sugeng Rade Oktari Sakti Rika Perdana Sari, Rika Perdana Saragih, Jenri Pujianto Sinria Kasna Sugeng Purwantoro E.S.G.S Valdo Franata Warnia Nengsih Wenda Novayani Yoanda Alim Syahbana Yohana Dewi Lulu Widyasari Yuliantoro, Heri R