Forecasting the Stock Price of PT. Dayamitra Telekomunikasi with Single Input Transfer Function Model

  • Resti Arsanti Statistics Study Program, Faculty of Mathematics and Natural Sciences, Universitas Tanjungpura, Indonesia
  • Neva Satyahadewi Statistics Study Program, Faculty of Mathematics and Natural Sciences, Universitas Tanjungpura, Indonesia https://orcid.org/0000-0001-8103-1797
  • Shantika Martha Statistics Study Program, Faculty of Mathematics and Natural Sciences, Universitas Tanjungpura, Indonesia https://orcid.org/0000-0001-6124-8534
Keywords: Transfer function; ARIMA; Forecasting; Stock Price; Trading Volume

Abstract

The unpredictable movement of stock prices is often a challenge for investors, so it requires a deeper understanding and consideration of various factors before making investment decisions. One of the factors that affect stock price movements is trading volume. Therefore, this study uses a single input transfer function model to forecast the daily closing stock price of PT. Dayamitra Telekomunikasi, with the closing stock price as the output variable and the stock trading volume as the input variable. The transfer function is a forecasting model that integrates ARIMA with multiple regression analysis, allowing modeling not only based on the values of the output variables, but also considering the influence of the input variables. ARIMA model estimation is performed on the input series for the prewhitening process, then the order of the transfer function is determined using cross-correlation plots, as well as model diagnostic tests to ensure its feasibility. Model accuracy is calculated to evaluate its performance in forecasting. The data used in this study are daily data from the period July 5, 2022 to October 9, 2024. The transfer function model obtained has an order of (2,0,0), with a MAPE value of 1.09%, which indicates that the model has good accuracy. Based on the forecasting results, it is estimated that there will be a decrease in the share price of PT. Dayamitra Telekomunikasi Tbk for the next five periods

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References

R. Antika, N. Satyahadewi, and H. Perdana, “Analisis pembentukan portofolio optimal menggunakan model Black–Litterman dengan pendekatan ARCH/GARCH,” Equator: Journal of Mathematical and Statistical Sciences, vol. 1, no. 1, p. 31, 2022, doi: 10.26418/ejmss.v1i1.59119.

A. Zakiah, E. Sulistianingsih, and N. Satyahadewi, “Geometric Brownian motion with jump diffusion and value at risk analysis of PT Bank Negara Indonesia stocks,” BAREKENG: Jurnal Ilmu Matematika dan Terapan, vol. 19, no. 1, pp. 617–628, Mar. 2025, doi: 10.30598/barekengvol19iss1pp617-628.

G. Aglia and R. Suhendah, “Analisis perbedaan harga saham, volume perdagangan saham dan kapitalisasi pada sektor manufaktur sebelum dan selama pandemi Covid-19,” Jurnal Multiparadigma Akuntansi, vol. 5, no. 2, pp. 831–841, Apr. 2023.

Y. Yanti and I. P. Dalimunthe, “Pengaruh volume perdagangan saham, abnormal return dan income smoothing terhadap harga saham,” COMPETITIVE Jurnal Akuntansi dan Keuangan, vol. 5, no. 1, pp. 222–233, 2021.

M. B. Wijayanti and Rosita, “Pengaruh volume perdagangan, nilai tukar rupiah, BI rate, inflasi terhadap harga saham perusahaan farmasi yang terdaftar di BEI selama Covid-19,” Jurnal Ekonomi Bisnis dan Akuntansi (JEBAKU), vol. 3, no. 3, pp. 27–39, Dec. 2023, doi: 10.55606/jebaku.v3i3.2565.

Sediono and D. Tito, “Peramalan jumlah penderita demam berdarah dengue di Kabupaten Jombang Jawa Timur dengan pendekatan fungsi transfer single input,” Jurnal Matematika, Statistika dan Komputasi, vol. 15, no. 2, pp. 10–19, 2019.

N. Alifia, E. Zukhronah, and Respatiwulan, “Peramalan jumlah uang kuasi di Indonesia dengan menggunakan fungsi transfer single input,” in Prosiding Seminar Nasional Aplikasi Sains & Teknologi (SNAST), 2021, pp. 29–38.

R. A. Pitaloka, Sugito, and R. Rahmawati, “Perbandingan metode ARIMA Box–Jenkins dengan ARIMA ensemble pada peramalan nilai impor Provinsi Jawa Tengah,” Jurnal Gaussian, vol. 8, no. 2, pp. 194–207, 2019, doi: 10.14710/j.gauss.8.2.194-207.

W. W. S. Wei, Time Series Analysis: Univariate and Multivariate Methods, 2nd ed. New York, NY, USA: Pearson/Addison-Wesley, 2006.

D. R. Febrianti, M. A. Tiro, and Sudarmin, “Metode vector autoregressive (VAR) dalam menganalisis pengaruh kurs mata uang terhadap ekspor dan impor di Indonesia,” VARIANSI: Journal of Statistics and Its Application on Teaching and Research, vol. 3, no. 1, p. 23, Mar. 2021, doi: 10.35580/variansiunm14645.

B. G. Prianda and E. Widodo, “Perbandingan metode seasonal ARIMA dan extreme learning machine pada peramalan jumlah wisatawan mancanegara ke Bali,” BAREKENG: Jurnal Ilmu Matematika dan Terapan, vol. 15, no. 4, pp. 639–650, Dec. 2021, doi: 10.30598/barekengvol15iss4pp639-650.

I. Muthahharah, “Peramalan indeks saham syariah Indonesia menggunakan autoregresive integrated moving average (ARIMA),” Jurnal MSA (Matematika dan Statistika serta Aplikasinya), vol. 7, no. 2, pp. 1–8, 2019.

L. Zhao, J. Mbachu, Z. Liu, and H. Zhang, “Transfer function analysis: Modelling residential building costs in New Zealand by including the influences of house price and work volume,” Buildings, vol. 9, no. 6, Art. no. 152, 2019, doi: 10.3390/buildings9060152.

F. D. Islami, A. Hoyyi, and D. Ispriyanti, “Pemodelan fungsi transfer dengan deteksi outlier untuk memprediksi nilai inflasi berdasarkan BI rate (Studi kasus BI rate dan inflasi periode Januari 2006 sampai Juli 2016),” Jurnal Gaussian, vol. 6, no. 3, pp. 323–332, 2017, doi: 10.14710/j.gauss.6.3.323-332.

Y. W. A. Nanlohy, B. S. S. Ulama, and S. W. Purnami, “Model fungsi transfer multi input untuk peramalan curah hujan di Kota Surabaya,” VARIANCE: Journal of Statistics and Its Applications, vol. 1, no. 2, pp. 82–92, Feb. 2020, doi: 10.30598/variancevol1iss2page82-92.

S. Yulianto and A. J. Najib, “Perbandingan metode SARIMA dan metode transfer pada produksi padi di Kabupaten Kendal,” in Seminar Nasional Official Statistics 2020, 2020, pp. 582–590.

D. R. Fitriani, M. Y. Darsyah, and R. Wasono, “Peramalan fungsi transfer single input pada harga emas pasar komoditi,” in Prosiding Seminar Nasional Pendidikan, Sains dan Teknologi, FMIPA Universitas Muhammadiyah Semarang, 2017, pp. 57–69.

Published
2025-11-29
How to Cite
Arsanti, R., Satyahadewi, N., & Martha, S. (2025). Forecasting the Stock Price of PT. Dayamitra Telekomunikasi with Single Input Transfer Function Model. Pattimura International Journal of Mathematics (PIJMath), 4(2), 87-96. https://doi.org/10.30598/pijmathvol4iss2pp87-96