Perbandingan Kinerja Long Short-Term Memory dan Gated Recurrent Unit dalam Prediksi Harga Saham McDonald’s

Muhammad Ridho Alfarid, Qonita Husnia Rahmah

Abstract


Social movements occurring at the global level can influence public perspectives and actions toward a company and affect its stock value. This study aims to analyze the impact of the social boycott movement on McDonald’s (McD) stock price by comparing the performance of the Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) models, with hyperparameter tuning conducted using Optuna. The data used consist of McD’s daily closing stock prices from January 31, 2015, to January 31, 2025, obtained from www.finance.yahoo.com. The results show that the LSTM model without hyperparameter tuning provides the most optimal performance, achieving a Mean Absolute Percentage Error (MAPE) of 1.79% on the training data and 1.47% on the test data. This model is effective in identifying changes and forecasting McD’s stock price before and after the boycott
 

Keywords


LSTM; GRU; Saham; Boikot; Optuna

Full Text:

PDF

References


K. Hisan, A. Gusnadi, F. Akmal, A. N. Aurelia, and S. S. Maesaroh, “Dampak Gerakan Boikot Pada Produk McDonald ’ s Indonesia Melalui Analisis,” Innov. J. Soc. Sci. Res., vol. 4, no. 3, pp. 19150–19163, 2024.

A. N. Sari, T. Maysiana, K. S. P. Mahanani, and R. Oktaviana, “Analisis Pemberitaan Donasi McDonalds Indonesia dalam Perspektif Framing dalam Public Relations,” Innov. J. Soc. Sci. Res., vol. 5, no. 1, 2025.

H. Nurdina, T. Akbar, and Y. R. Y. N. Nugraha, “Dampak Boikot Konsumen terhadap Fluktuasi Harga Saham Starbucks: Analisis Empiris,” JAProf J. Adm. Prof., vol. 5, no. 2, pp. 109–121, 2024.

W. Budiharto, “Data science approach to stock prices forecasting in Indonesia during Covid ‑ 19 using Long Short ‑ Term Memory ( LSTM ),” J. Big Data, vol. 8, no. 47, pp. 1–9, 2021, doi: 10.1186/s40537-021-00430-0.

N. Khairunisa and P. Hendikawati, “Long Short-Term Memory and Gated Recurrent Unit for Stock Price Prediction,” J. Mat. Stat. dan Komputasi, vol. 21, no. 1, pp. 321–333, 2024, doi: 10.20956/j.v21i1.35930.

E. Ismanto, “LSTM Network Hyperparameter Optimization for Stock Price Prediction Using the Optuna Framework,” J. Ilm. Tek. Elektro Komput. dan Inform., vol. 9, no. 1, pp. 22–35, 2023, doi: 10.26555/jiteki.v9i1.24944.

E. K. M. Uskono, “Aplikasi Metode ARIMA, LSTM, dan Hybrid ARIMA-LSTM pada Peramalan Harga Crude Palm Oil (CPO) Dunia,” IPB University, 2023.

NURPADIAN, “PERAMALAN HARGA MINYAK MENTAH WEST TEXAS INTERMEDIATE MENGGUNAKAN METODE GATED RECURRENT UNIT,” UNIVERSITAS HASANUDDIN, 2024.

M. Lim, T. Handayani, T. Informatika, F. T. Informasi, and U. Tarumanagara, “Penerapan LSTM dan GRU untuk Prediksi Harga Cabai Merah di Kota Jawa Timur,” vol. 13, no. 2, pp. 1408–1416, 2025.

J. A Ilemobayo et al., “Hyperparameter Tuning in Machine Learning: A Comprehensive Review,” J. Eng. Res. Reports, vol. 26, no. 6, pp. 388–395, 2024, doi: 10.9734/jerr/2024/v26i61188.

A. Tikaningsih, P. Lestari, A. Nurhopipah, I. Tahyudin, E. Winarto, and N. Hassa, “Optuna Based Hyperparameter Tuning for Improving the Performance Prediction Mortality and Hospital Length of Stay for Stroke Patients,” Telematika, vol. 17, no. 1, pp. 1–16, 2024, doi: 10.35671/telematika.v17i1.2816.

A. T. Nurani, A. Setiawan, and B. Susanto, “Perbandingan Kinerja Regresi Decision Tree dan Regresi Linear Berganda untuk Prediksi BMI pada Dataset Asthma,” J. Sains dan Edukasi Sains, vol. 6, no. 1, pp. 34–43, 2023, doi: 10.24246/juses.v6i1p34-43.

A. Nurfadilah, W. Budi, E. Kurniati, and D. Suhaedi, “Penerapan Metode Moving Average untuk Prediksi Indeks Harga Konsumen,” J. Mat., vol. 21, no. 1, pp. 19–25, 2022, [Online]. Available: https://journals.unisba.ac.id/index.php/matematika/article/view/337%0Ahttps://journals.unisba.ac.id/index.php/matematika/article/download/337/528

D. C. Montgomery, C. L. Jennings, and M. Kulahci, Introduction to Time Series Analysis and Forecasting. Canada: John Wiley, Sons, 2015.

N. Azizah, “CEO McDonalds Nyatakan Aksi Boikot Berdampak Parah Pada Bisnis,” Republika, Indonesia, Jan. 06, 2024. [Online]. Available: https://internasional.republika.co.id/berita/s6tce6463/ceo-mcdonalds-nyatakan-aksi-boikot-berdampak-parah-pada-bisnis#:~:text=REPUBLIKA.CO.ID%2C YERUSALEM -- CEO McDonald%27s Chris Kempczinski menyatakan,telah terkena dampak seruan boikot untuk mendukung

A. F. Nugraha, Y. Pristyanto, and I. Pratama, “Penanganan Missing Values Untuk Meningkatkan Kinerja Model Machine Learning Pada Data Telemarketing,” Pseudocode, vol. 7, no. 2, pp. 165–171, Sep. 2020, doi: 10.33369/pseudocode.7.2.165-171.




DOI: https://doi.org/10.37905/jjps.v7i1.33060

Refbacks

  • There are currently no refbacks.


Copyright (c) 2026 Jambura Journal of Probability and Statistics

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.


Editorial Office of Jambura Journal of Probability and Statistics:
 
Department of Statistics, 3rd Floor Faculty of Mathematics and Natural Sciences, Universitas Negeri Gorontalo
Jl. Prof. Dr. Ing. B.J Habibie, Tilongkabila Kabupaten Bone Bolango, 96119
Telp: +6285398740008 (Call/SMS/WA)
E-mail: [email protected]