EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 678 (2025) E3S Web Conf., 678 (2025) 05001 References
Open Access
Issue
E3S Web Conf.
Volume 678, 2025
The 2nd International EcoHarmony Summit (IES 2025): Green Transitions and Innovations for a Sustainable Tomorrow
Article Number 05001
Number of page(s) 13
Section Sustainability Accounting and Green Finance
DOI https://doi.org/10.1051/e3sconf/202567805001
Published online 16 December 2025
  1. A. Anwar, S. Hidayatullah, and Z. Ruma, Analisis portofolio optimal dengan model Markowitz pada perusahaan sektor basic materials di BEI. J. Sekuritas 6, 135–148 (2023). [Google Scholar]
  2. Y. S. J. Nasution, Peranan pasar modal dalam perekonomian negara. Human Falah 2, 95–112 (2015). [Google Scholar]
  3. R. G. Ayuningrum, M. U. Mai, and R. P. K. Dewi, Dampak kinerja keuangan terhadap return saham dengan inflasi sebagai variabel moderasi pada sektor industri barang konsumsi kategori syariah di Bursa Efek Indonesia. J. Appl. Islam. Econ. Finance 2, 151–163 (2021). https://doi.org/10.35313/jaief.v2i1.2892 [Google Scholar]
  4. X. Wan, S. A. A. Kazmi, and C. Y. Wong, Manufacturing, exports, and sustainable growth: Evidence from developing countries. Sustainability 14, 1646 (2022). https://doi.org/10.3390/su14031646 [Google Scholar]
  5. Kementerian Perindustrian Republik Indonesia, IKI Januari 2023 meningkat tajam, industri optimis tumbuh lebih tinggi di tahun 2023. (2021). https://kemenperin.go.id/ [Google Scholar]
  6. B. Y. Pandji, I. Indwiarti, and A. A. Rohmawati, Perbandingan prediksi harga saham dengan model ARIMA dan artificial neural network. Indones. J. Comput. 4, 1–8 (2019). [Google Scholar]
  7. P. Kumar and G. Santhya, Role of financial intermediaries in capital market. J. Contemp. Issues Bus. Gov. 26, (2021). https://doi.org/10.47750/cibg.2020.26.02.085 [Google Scholar]
  8. D. A. Rezaldi and S. Sugiman, Peramalan metode ARIMA data saham PT Telekomunikasi Indonesia. In Proc. Seminar Nasional Matematika (2021), 611–620. [Google Scholar]
  9. D. A. Ramdani and F. N. Azizah, Analisis perbandingan peramalan permintaan pelumas PT XYZ dengan metode moving average, exponential smoothing, dan naive method. In Proc. Seminar Nasional Official Statistics (2019), 1000-1010. [Google Scholar]
  10. F. M. Yusof, R. Razali, N. Z. Zainuddin, and R. Razali, The impact of fundamental factors on stock returns of industrial sector Islamic stocks in Indonesia. J. Islam. Finance 9, 99–113 (2020). [Google Scholar]
  11. S. Nisa, R. Rahmi, and I. Ramadhan, Analisis fundamental saham syariah pada perusahaan sektor industrial di Bursa Efek Indonesia. J. Ekon. Keuangan 8, 85–98 (2022). [Google Scholar]
  12. H. Erkekoglu, A. P. M. Garang, and A. S. Deng, Comparative evaluation of forecast accuracies for ARIMA, exponential smoothing and VAR. Int. J. Econ. Financ. Issues 10, 206–216 (2020). https://doi.org/10.32479/ijefi.9020 [Google Scholar]
  13. H. Hersugondo, I. Ghozali, E. Handriani, T. Trimono, and I. D. Pamungkas, Price index modeling and risk prediction of Sharia stocks in Indonesia. Economies 10, 17 (2022). https://doi.org/10.3390/economies10010017 [Google Scholar]
  14. B. Usman, M. G. Hasnam, R. Nurazi, Baihaqi, and S. Aujirapongpan, Exploring investor attention in Shariah markets, macroeconomic influences, and corporate performance: Insights from Indonesia. Soc. Sci. Humanit. Open 10, 101015 (2024). https://doi.org/10.1016/j.ssaho.2024.101015 [Google Scholar]
  15. S. Tabot Enow, Valuing equity securities using fundamental analysis: Evidence from international stock markets. Int. J. Res. Bus. Soc. Sci. 12, 478–489 (2023). https://doi.org/10.20525/ijrbs.v12i6.2644 [Google Scholar]
  16. K. Khotimah and I. Murtaqi, The fundamental analysis of Indonesian stock return (case study: listed public companies in sub-sector food and beverage for the period 2003-2012). J. Bus. Manag. 4, 67–75 (2015). https://journal.sbm.itb.ac.id/index.php/jbm/article/view/1391 [Google Scholar]
  17. L. Judijanto, C. R. Elisabeth, F. A. Nugroho, and T. Purwaningtyas, Fundamental analysis and risk management mechanisms on investment returns and investor satisfaction in the Indonesian capital market. West Sci. Interdiscip. Stud. 3, 15–26 (2023). https://doi.org/10.58812/wsis.v3i01.162 [Google Scholar]
  18. R. R. Sharma, M. Kumar, S. Maheshwari, and K. P. Ray, EVDHM-ARIMA-based time series forecasting model and its application for COVID-19 cases. IEEE Trans. Instrum. Meas. 70, 1–10 (2021). https://doi.org/10.1109/TIM.2020.3041833 [Google Scholar]
  19. M. F. Rizvi, ARIMA model time series forecasting. Int. J. Res. Appl. Sci. Eng. Technol. 12, 3782–3785 (2024). https://doi.org/10.22214/ijraset.2024.62416 [Google Scholar]
  20. J. Fattah, L. Ezzine, Z. Aman, H. El Moussami, and A. Lachhab, Forecasting of demand using ARIMA model. Int. J. Eng. Bus. Manag. 10, 1–8 (2018). https://doi.org/10.1177/1847979018808673 [Google Scholar]
  21. E. Pujiati, D. Yuniarti, and R. Goejantoro, Peramalan dengan menggunakan metode double exponential smoothing dari Brown (studi kasus: Indeks Harga Konsumen (IHK) Kota Samarinda). J. Eksponensial 7, 1–10 (2016). [Google Scholar]
  22. N. A. M. Noor and N. H. A. Rahman, Exponential smoothing constant determination to minimize the forecast error. Math. Model. Comput. 9, 50–56 (2022). https://doi.org/10.23939/mmc2022.01.050 [Google Scholar]
  23. I. G. B. Ngurah Diksa, Peramalan gelombang COVID-19 menggunakan hybrid nonlinear regression logistic-double exponential smoothing di Indonesia dan Prancis. Jambura J. Math. 3, 37–51 (2021). https://doi.org/10.34312/iiom.v3i1.7771 [Google Scholar]
  24. A. Muchayan, Comparison of Holt and Brown's double exponential smoothing methods in the forecast of moving price for mutual funds. J. Appl. Sci. Eng. Technol. Educ. 1, 183–192 (2019). https://doi.org/10.35877/454RI.asci1167 [Google Scholar]
  25. A. Rahmawati, C. N. Ramadhanti, F. H. Ismia, and R. Nurcahyo, Comparing the accuracy of Holt's and Brown's double exponential smoothing method in forecasting the coal demand of Company X. In Proc. Int. Conf. Ind. Eng. Oper. Manag., Michigan, USA (2021). https://doi.org/10.46254/IN01.20210117 [Google Scholar]
  26. D. Chicco, M. J. Warrens, and G. Jurman, The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation. Peer J Comput. Sci. 7, e623 (2021). https://doi.org/10.7717/peeri-cs.623 [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.