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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Bina Insani ICT Journal JKTP: Jurnal Kajian Teknologi Pendidikan JTP - Jurnal Teknologi Pendidikan EXPLORE Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi bit-Tech Jurnal ABDIMAS (Pengabdian kepada Masyarakat) UBJ JUTECH : Journal Education and Technology EXPLORE Jurnal Ticom: Technology of Information and Communication Jurnal Pengabdian Masyarakat Tekno
Lucia Sri Istiyowati
Institut Keuangan Perbankan Dan Informatika Asia Perbanas
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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IMPLEMENTASI DATA MINING DALAM PREDIKSI HARGA SAHAM BBNI DENGAN PEMODELAN MATEMATIKA MENGGUNAKAN METODE LSTM DENGAN OPTIMASI ADAM Rahman, Alrafiful; Istiyowati, Lucia Sri; Valentinus, Valentinus; Ivan, Ivan; Azis, Zainal
JUTECH : Journal Education and Technology Vol 5, No 2 (2024): JUTECH DESEMBER
Publisher : STKIP Persada Khatulistiwa Sintang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31932/jutech.v5i2.4137

Abstract

Stock price prediction plays a crucial role in investment decision-making, allowing investors to maximize profits and minimize risks. This study implements the Long Short-Term Memory (LSTM) method with Adam optimization to predict the stock price of Bank Negara Indonesia (BBNI) based on historical stock price data from the Indonesia Stock Exchange (2001-2023). LSTM is chosen for its ability to handle sequential data and identify long-term patterns in time series. Meanwhile, the Adam optimization algorithm is used to accelerate model convergence and improve prediction accuracy. The data used includes daily stock prices (closing prices), and the research process involves data collection, preprocessing, LSTM model creation, Adam optimization, training, evaluation, and prediction. The experimental results show that the model with a batch size of 64 and 100 epochs yields an R² of 0.9928 and a MAPE of 1.53%, indicating a very high prediction accuracy. With an accuracy of 98.46%, the LSTM model with Adam optimization proves to be effective in predicting stock prices, providing excellent results for applications in investment strategies. This study demonstrates the great potential of applying data mining and machine learning techniques in more informed and data-driven stock market analysis.
Metaverse-Based Learning in the Digital Era Jusuf, Heni; Lucia Sri Istiyowati; Muh Fauzi; Maria Magdalena; R. Eko Indrajit
JTP - Jurnal Teknologi Pendidikan Vol. 25 No. 3 (2023): Jurnal Teknologi Pendidikan
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat, Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/jtp.v25i3.35071

Abstract

Digital disruption in the world of education refers to the impact of technology on traditional education systems and models, where the current education system is felt to need to be adjusted to the progress of the times and the needs of students. The business model of education in this digital era requires the innovation and creativity of teachers. After the Covid 19 pandemic, in addition to providing challenges in the world of education, it also provides an opportunity where students and educators are accustomed to online learning applications, teleconference applications, or collaboration applications that were previously not or rarely used by the world of Education. Many apps have been created to make online learning easier. Metaverse has been around since 2010, but due to the pandemic, the use of metaverse in learning is again being used with the development of Virtual reality, extended reality, and augmented reality technology. These three technologies can display a virtual environment just like the original environment. The method used to design metaverse-based learning is to use the ADDIE research and development model while learning development follows the stages of the Dick and Carey model. The results of field trials using survey methods and experiments on 20 junior high school students for one semester using the metaverse, resulted in a score of 4.82 with the conclusion of excellent learning material, students felt very happy, motivated to complete tasks, and always followed the learning stages designed in the form of games. Implementing the metaverse in learning can increase student engagement, creativity, technology skills, collaboration, and interaction as well as improve learning experiences that are more fun and engaging.
Co-Authors - Sriasih Agnes Novita Azis, Zainal Dazki, Erick Elliana Gautama Harmawan, Toga Ari Heni Jusuf Ivan Ivan Kumalasari, Rati Manik , Chrismanto Natanail Margaret Teacher Banjarnahor Maria Magdalena Maria Magdalena Muh Fauzi Mukti, Muhammad Ivan Nani Krisnawaty Tachjar Pratiwi Purbaratri, Winny R. Eko Indrajit Rahman, Alrafiful Ranien, Zahwa Bunga Rati Kumalasari Santoso, Handri Sriasih, Sriasih Tiolina Evi Valentinus, Valentinus Yunus Widjaja Yunus Widjaja