A Comparative Analysis of ARIMA Models Based on Data Period and Frequency at PT Midi Utama Indonesia Tbk

Authors

  • Aprilia Prastianti Universitas Cenderawasih, Indonesia
  • Dwi Putri Nanda Universitas Cenderawasih, Indonesia
  • Marcella Lolo Langi' Universitas Cenderawasih, Indonesia

DOI:

https://doi.org/10.24256/kharaj.v8i3.11099

Keywords:

ARIMA, forecasting, stock price, Midi Utama Indonesia, MAPE

Abstract

Uncertainty in short-term investment decision-making. This study aims to analyze the daily stock price movement of PT Midi Utama Indonesia Tbk and to determine the feasibility of the ARIMA model for forecasting stock prices. The study employed a quantitative time series approach using daily closing price data over a 3-year period with daily frequency observations. The analysis was conducted using RStudio through descriptive statistics, stationarity testing, first-order differencing, ACF and PACF identification, ARIMA model selection, diagnostic testing, and forecast accuracy evaluation. The results indicate that the data were non-stationary at the level because the Augmented Dickey-Fuller test produced a p-value of 0.4372. After first differencing, the p-value decreased to 0.0100, indicating that the data had become stationary. The best model identified was ARIMA (1,1,1) because it had the lowest AIC value among the compared models. The Ljung-Box test yielded a p-value of 0.7116, indicating that there was no residual autocorrelation. The model produced an MAE of 6.10853, an RMSE of 8.97241, and a MAPE of 2.43817%, indicating that the model is highly accurate with an error rate below 8%. These findings demonstrate that the ARIMA (1,1,1) model is suitable for short-term forecasting of PT Midi Utama Indonesia Tbk stock prices.

References

Gazali, M. M., & Setiawan, H. (2025). Application of the ARIMA Model to Forecast the Daily Opening Price of PT. Bank Central Asia Tbk. Stock. Digital Transformation Technology, 5(1), 278–289. https://doi.org/10.47709/digitech.v5i1.6129

Khoirayanti, R. N., & Sulistiyo, H. (2020). THE EFFECT OF STOCK PRICE, TRADING VOLUME, AND TRADING FREQUENCY ON THE BID-ASK SPREAD. JIAFE (Journal of Accounting, Faculty of Economics), 6(2), 231–240. https://doi.org/10.34204/jiafe.v6i2.2305

La Murdani, A. I., & Nanlohy, Y. W. A. (2022). IMPLEMENTATION OF THE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) MODEL FOR FORECASTING THE NUMBER OF SHIP PASSENGERS AT THE PORT OF AMBON. VARIANCE: Journal of Statistics and Its Applications, 3(2), 81–90. https://doi.org/10.30598/variancevol3iss2page81-90

Qalbi, A., Nurfadilah, K., & Alwi, W. (2021). Comparison of Fuzzy Time Series Methods and Autoregressive Integrated Moving Average (ARIMA) for Inflation Data. EIGEN MATHEMATICS JOURNAL, 40–50. https://doi.org/10.29303/emj.v4i2.122

Saluza, I., Sartika, D., Astuti, L. W., Faradillah, F., Desitama, L., & Purnamasari, E. D. (2021). Prediction of Stock Closing Price Time Series Data Using the Box-Jenkins ARIMA Model. Global Informatics Scientific Journal, 12(2). https://doi.org/10.36982/jiig.v12i2.1940

Sudipa, I. G. I., Riana, R., Putra, I. N. T. A., Yanti, C. P., & Aristana, M. D. W. (2023). Trend Forecasting of the Top 3 Indonesian Bank Stocks Using the ARIMA Method. SinkrOn, 8(3), 1883–1893. https://doi.org/10.33395/sinkron.v8i3.12773

Zidan Rusminto, M., Adi Wibowo, S., & Santi Wahyuni, F. (2024a). STOCK PRICE FORECASTING USING THE ARIMA (AUTOREGRESSIVE INTEGRATED MOVING AVERAGE) TIME SERIES METHOD. JATI (Journal of Computer Science Students), 8(2), 1263–1270. https://doi.org/10.36040/jati.v8i2.9089

Zidan Rusminto, M., Adi Wibowo, S., & Santi Wahyuni, F. (2024b). STOCK PRICE FORECASTING USING THE ARIMA (AUTOREGRESSIVE INTEGRATED MOVING AVERAGE) TIME SERIES METHOD. In Journal of Computer Engineering Students (Vol. 8, No. 2).

Downloads

Published

2026-07-07

How to Cite

Prastianti, A., Nanda, D. P., & Langi’, M. L. (2026). A Comparative Analysis of ARIMA Models Based on Data Period and Frequency at PT Midi Utama Indonesia Tbk. Al-Kharaj: Journal of Islamic Economic and Business, 8(3). https://doi.org/10.24256/kharaj.v8i3.11099

Citation Check

Similar Articles

<< < 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 > >> 

You may also start an advanced similarity search for this article.