Forecasting Health Sector Stock Prices using ARIMAX Method

Authors

  • Muhammad Aprilianto Universitas Labuhanbatu, Indonesia
  • Mila Nirmala Sari Hasibuan Universitas Labuhanbatu, Indonesia
  • Syaiful Zuhri Harahap Universitas Labuhanbatu, Indonesia

DOI:

10.33395/sinkron.v7i2.11418

Abstract

In daily stock trading activities, stock prices can experience ups and downs. The rise and fall of stock prices occurs due to changes in supply and demand for these shares. The COVID-19 pandemic did not have a negative effect, instead it had a positive impact on stock prices in health companies. companies in the health sector experienced a fairly good profit of 10.46% in the fourth quarter of 2021. This fact made investors interested in buying shares in companies in the health sector in the hope of selling them when demand increased, resulting in doubled profits. Stock conditions continue to fluctuate every day, making investors need to pay attention and study the past data of the health sector company that will be selected before deciding to invest. Therefore, it is necessary to forecast stock prices in the health sector for the next several periods as a step in making investment decisions. The health sector companies that will be modeled are PT Kimia Farma (Persero) Tbk and PT Kalbe Farma Tbk. The method used in this study is the ARIMAX model. The test and analysis results show that based on the RMSE and MAPE values, the best model is ARIMAX(5,13) for PT Kalbe Farma Tbk shares with a MAPE value of 1% in in-sample data and 0.6% in out-sample data.

GS Cited Analysis

Downloads

Download data is not yet available.

References

Amanda, T. R., Ahmar, N., Sailendra, & Merawati, E. E. (2019). Dampak COVID-19 Terhadap Tren Sektoral Harga Saham Syariah di Indonesia. Fair Value : Jurnal Ilmiah Akuntansi Dan Keuangan, 1(2), 307–313. Retrieved from http://journal.uin-alauddin.ac.id/index.php/Iqtisaduna/article/view/20214

Arfan, A., & ETP, L. (2019). Prediksi Harga Saham di Indonesia Menggunakan Algoritma Long Short-Term Memory. SeNTIK, 3(1), 225–230.

Aziz, M. A. A., Kamaludin, A., & Pudjiastuti, S. (2020). PENGARUH INDEKS HARGA KONSUMEN, INFLASI, DAN BI RATE PADA INDEKS HARGA SAHAM SYARIAH SEKTOR KESEHATAN Malik. Iqtisadiya: Jurnal Ilmu Ekonomi Islam, 7(14), 61–74. Retrieved from https://journal.uinsgd.ac.id/index.php/iqtisadiya/article/view/10169

BPS. (2021). Pertumbuhan Ekonomi Indonesia Triwulan IV-2020. In www.bps.go.id. Retrieved from https://www.bps.go.id/pressrelease/2021/02/05/1811/ekonomi-indonesia-2020-turun-sebesar-2-07-persen--c-to-c-.html

Dash, R., & Dash, P. K. (2017). Chapter 25 - MDHS–LPNN: A Hybrid FOREX Predictor Model Using a Legendre Polynomial Neural Network with a Modified Differential Harmony Search Technique (P. Samui, S. Sekhar, & V. E. B. T.-H. of N. C. Balas, eds.). Academic Press. https://doi.org/https://doi.org/10.1016/B978-0-12-811318-9.00025-9

Du, Y. (2018). Application and analysis of forecasting stock price index based on combination of ARIMA model and BP neural network. 2018 Chinese Control And Decision Conference (CCDC), 2854–2857. https://doi.org/10.1109/CCDC.2018.8407611

Fadilah, W. R. U., Agfiannisa, D., & Azhar, Y. (2020). Analisis Prediksi Harga Saham PT. Telekomunikasi Indonesia Menggunakan Metode Support Vector Machine. Fountain of Informatics Journal, 5(2), 45. https://doi.org/10.21111/fij.v5i2.4449

Hossain, M. S., Ahmed, S., & Uddin, M. J. (2021). Impact of weather on COVID-19 transmission in south Asian countries: An application of the ARIMAX model. Science of The Total Environment, 761, 143315. https://doi.org/https://doi.org/10.1016/j.scitotenv.2020.143315

Jing, Q. L., Cheng, Q., Marshall, J. M., Hu, W. B., Yang, Z. C., & Lu, J. H. (2018). Imported cases and minimum temperature drive dengue transmission in Guangzhou, China: evidence from ARIMAX model. Epidemiology and Infection, 146(10), 1226–1235. https://doi.org/10.1017/S0950268818001176

Ling., A. S. C., Darmesah, G., Chong, K. P., & Ho, C. M. (2019). Application of ARIMAX Model to Forecast Weekly Cocoa Black Pod Disease Incidence. Mathematics and Statistics, 7(4), 29–40. https://doi.org/10.13189/ms.2019.070705

Ma, C. C. Y., & Iqbal, M. (1984). Statistical comparison of solar radiation correlations Monthly average global and diffuse radiation on horizontal surfaces. Solar Energy, 33(2), 143–148. https://doi.org/https://doi.org/10.1016/0038-092X(84)90231-7

Maricar, M. A. (2019). Analisa Perbandingan Nilai Akurasi Moving Average dan Exponential Smoothing untuk Sistem Peramalan Pendapatan pada Perusahaan XYZ. Jurnal Sistem Dan Informatika, 13(2), 36–45.

Purnama, J., & Juliana, A. (2019). Analisa Prediksi Indeks Harga Saham Gabungan Menggunakan Metode Arima. Cakrawala Management Business Journal, 2(2), 454. https://doi.org/10.30862/cm-bj.v2i2.51

Rusyida, W. Y., & Pratama, V. Y. (2020). Prediksi Harga Saham Garuda Indonesia di Tengah Pandemi Covid-19 Menggunakan Metode ARIMA. Square : Journal of Mathematics and Mathematics Education, 2(1), 73. https://doi.org/10.21580/square.2020.2.1.5626

Suyudi, M. A. D., Djamal, E. C., & Maspupah, A. (2019). Prediksi Harga Saham menggunakan Metode Recurrent Neural Network. Seminar Nasional Aplikasi Teknologi Informasi (SNATi), 33–38.

Untoro, A. B. (2020). Prediksi Harga Saham Dengan Menggunakan Jaringan Syaraf Tiruan. Jurnal Teknologi Informatika Dan Komputer, 6(2), 103–111. https://doi.org/10.37012/jtik.v6i2.212

Wei, W. (2006). Time Series Analysis: Univariate and Multivariate Methods, 2nd edition, 2006.

Downloads


Crossmark Updates

How to Cite

Aprilianto, M., Hasibuan, M. N. S. ., & Harahap, S. Z. . (2022). Forecasting Health Sector Stock Prices using ARIMAX Method. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 6(2), 641-648. https://doi.org/10.33395/sinkron.v7i2.11418

Most read articles by the same author(s)

1 2 > >>