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Journal : Jurnal Pepadun

HYBE Corporation Stock Price Prediction Using CNN-LSTM with CRISP-DM Framework Hidayah, Nurul; Khaira, Ulfa; Bintana, Rizqa Raaiqa
Jurnal Pepadun Vol. 7 No. 1 (2026): April
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/pepadun.v7i3.297

Abstract

Digital transformation in financial analysis requires the application of computational models that can handle the complexity of the stock market efficiently and objectively. This study aims to predict the stock price of HYBE Corporation using the Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) model within the CRISP-DM (Cross Industry Standard Process for Data Mining) framework. The data used consists of daily stock prices of HYBE Corporation obtained from Yahoo Finance. The research process includes the main stages of CRISP-DM, namely business understanding, data understanding, data preparation, modeling, evaluation, and presentation of results. The CNN-LSTM model is designed to combine the ability of CNN to extract local patterns from time series with the advantage of LSTM in capturing long-term dependencies. To maximize the parameters used, this study also performed hyperparameter tuning using GridSearchCV on several key parameters. This process aimed to obtain the best combination of parameters capable of improving prediction accuracy and reducing the error value in the CNN-LSTM model. The evaluation results show that the CNN-LSTM model is capable of providing predictions with a very high level of accuracy. The Mean Squared Error (MSE) value is 0.00029, the Root Mean Squared Error (RMSE) is 0.01704, the Mean Absolute Error (MAE) is 0.01346, and the Mean Absolute Percentage Error (MAPE) is 2.15%. These low evaluation values demonstrate the model's effectiveness in handling stock market volatility while maintaining stability in predicting both short-term and long-term patterns.
Co-Authors Abidin, Zainil Akhiyar Waladi Aliyah, Rihhadatul Amanda Iza Sofiani Amisha Dewi, Agnela Anisa Bella Panjaitan Anna Febriane Angelica Arsa, Daniel Aryani, Reni Benedika Ferdian Hutabarat Bisma Aulia Bisma Aulia Cepi Ramdan Cepi Ramdan Christina Mutiara Ishak Desi Hartati Desi Musfiroh Devi Listiani Safitri Dewi Lestari Dinda Fatimah Sarah Edi Saputra Edi Saputra Eko Prasetyo Eko Prasetyo Utomo, Pradita Elfira Elfira Elsha Aureal Shopia Fitri Dwi Lestari Ghaitsa Althafah Wandira Ghaitsa Althafah Wandira Guntoro Guntoro Guntoro Guntoro Haezrah Oktavini Hasanatul Iftitah Hasby Kuswanto Hidayat Hidayat Imelda Raudati Imelda Raudati Indra Weni Indryani Indryani Insyra Inayah Putri Jefri Marzal Krisman Pratama Simanjuntak Lailan Syaufina Lesianda Junitia Lilian Putri Salsabila M. Rizky Ardiansyah Putra Mardhotillah, Bunga Mauladi Mauladi Muazzomi, Nyimas Muhammad Alfares Muhammad Rumii Firnanditya Muksin Alfalah Mustakim Mustakim Mutia Fadhila Putri Muttaqin, Rizki Daffa Nabila Febrisa Anggraini Nasution, Afdal Aditya Nasution, Mukhtada Billah Nazwa Eka Hervy Notasonda Soni Putra Nugroho Ardy Pramono NURUL HIDAYAH Nyimas Azzahra Nur Saiyidah Nafisah Odista Dwi Putra Pebrianto, Dony Yusra Pikir Claudia Septiani Gulo Putri Hazmawati Qodri, Muhammad Amin Ragil Johanda Ramadhani, Hana Oktavia Ramadhani, Selvi Ayu Reza Wahyu Hardian Rio Gilang, Divo Riyan Ardani Rizki Surya Amanda Rizqa Raaiqa Bintana Robertus Herodian Sitanggang Robi Purnomo Rosyadi, Akhmad Fikri Samratul Fuady Sitanggang, Imas S. Sulistiyo, Urip Syalsabylla Syalsabylla Syamsyida Rozi Tasia Maidi Saputri Tasia Maidi Saputri Taufik Hidayat Tesa Ananda Putri Tri Suratno Uswatul Hasni Utomo, Pradita Eko Prasetyo Valerina Noa Verent Wisard Widsli Kalengkongan Yolla Noverina Yosi Riduas Hais Yosika Dian Saputri Yuanita Clark Lestari Simbolon Yurinanda, Sherli