Fundamental Analysis and Stock Price Forecasting Using the Autoregressive Integrated Moving Average Method at PT AKR Corporindo Tbk

Novelyarosa Ambar Chelsea Pailah; Muthia Putri Awalia; Riene Elisabeth Infasye Womsiwor; Salsabila Farsya Fadhilah Hairuddin; Radian Januari Situmeang; Kurniawan Patma

doi:10.54471/muhasabatuna.v8i1.3930

Authors

Novelyarosa Ambar Chelsea Pailah Universitas Cenderawasih
Muthia Putri Awalia Universitas Cenderawasih
Riene Elisabeth Infasye Womsiwor Universitas Cenderawasih
Salsabila Farsya Fadhilah Hairuddin Universitas Cenderawasih
Radian Januari Situmeang Universitas Cenderawasih
Kurniawan Patma Universitas Cenderawasih

DOI:

https://doi.org/10.54471/muhasabatuna.v8i1.3930

Keywords:

Stock Price Forecasting, ARIMA, Fundamental Analysis

Abstract

This research basically aims to see where AKRA's stock price will move in the future, and the tool chosen to answer that is the ARIMA statistical method, which stands for Autoregressive Integrated Moving Average. The research has two goals: first, to build the most suitable model, and second, to use that model to predict AKRA's stock price, so investors aren't too in the dark when making decisions. The data used is sourced from Yahoo Finance, specifically the daily closing prices of AKRA stock ranging from 2021 to 2026. That time span is actually enough to capture various dynamics that occur, and the format in the form of a time series is perfect to be used as material for analyzing this model. The preparation steps themselves are not short; there are several stages that must be passed one by one and cannot be skipped carelessly. Initially, the data is checked to see if it is stationary or not through the ADF test. From there, the ACF and PACF charts are examined to read patterns and determine a reasonable model structure. To determine which model is the best, the reference is the AIC value. After selecting the model, the residuals are not immediately ignored; they are checked again through diagnostic tests to ensure nothing is overlooked. All of this is done in RStudio. The hope is that from this rather convoluted process, this study can provide a fairly clear picture of future AKRA price trends, through a valid ARIMA model that can be relied upon for projections over several upcoming periods.

References

Aini, K. N., Rahmadini, S. O., Arifin, F., Ria, R., & Hasibuan, A. (2026). Perkembangan Perekonomian Indonesia dan Implikasinya Terhadap Kesejahteraan Masyarakat. 1–13.

Derivat, J. (2024). Peramalan Harga Saham PT . Bank Central Asia , Tbk. 11(1), 54–63.

Djami, R. J., & Latupeirissa, S. J. (2020). PERAMALAN HARGA EMAS DI INDONESIA TAHUN 2014-2019 DENGAN METODE ARIMA BOX-JENKINS (Forecasting Gold Prices in Indonesia 2014-2019 Using ARIMA Box-Jenkins Method ). 2, 53–62.

Dwi, R., & Hidayati, N. (2025). Implementasi Model ARIMA untuk Analisa Prediksi Harga Penutupan Saham Historis Harian Perusahaan BP Minyak dan Gas Multinasional Implementation of ARIMA Model for Daily Historical Stock Closing Price Prediction Analysis of BP Oil and Gas Multinational Company. 13(3).

https://doi.org/10.26418/justin.v13i3.90747

Fadila, A. N., & Nuswandari, C. (2022). Apa Saja Faktor – Faktor Yang Mempengaruhi Harga Saham ? 15(2), 283–293.

Hope, E., & Nation, E. (2025). Mengusung Cita , Membangun Bangsa.

Kakombohi, A. P., Prang, J. D., & Salaki, D. T. (n.d.). d ’ CartesiaN Jurnal Matematika dan Aplikasi Prediksi Harga Saham PT AKR Corporindo Tbk ( AKRA . JK ) Menggunakan Model ARIMA-GARCH.

Kategori, K., Menurut, S., & Lynch, P. (2023). ANALISIS PERBANDINGAN MODEL ARIMA DAN LSTM DALAM PERAMALAN HARGA PENUTUPAN SAHAM ( STUDI KASUS : 6. 2(6).

Ke, W., & Sabang, K. (2025). STATMAT (Jurnal Statistika dan Matematika). 7(3), 279–291.

Kurniasi, A. A., Saptari, M. A., Ilhadi, V., Studi, P., Informasi, S., Teknik, F., Malikussaleh, U., &

Efek, B. (2020). APLIKASI PERAMALAN HARGA SAHAM PERUSAHAAN LQ45 DENGAN

MENGGUNAKAN. November 2019, 13–26.

Lhokseumawe, I. (2023). No Title. 7(2), 141–151.

Lubis, N. H., Syahinda, T. R., Adrio, E., Ria, R., Hasibuan, A., Islam, P. E., Islam, U., & Sumatera, N.

(2026). Kontribusi Pasar Modal Indonesia Terhadap Pertumbuhan dan Stabilitas Perekonomian Nasional Kontribusi Pasar Modal Indonesia Terhadap Pertumbuhan dan Stabilitas Perekonomian. 162–171.

Marshella, S. H., & Risyahputri, A. (2025). IMPLEMENTASI METODE ARIMA DALAM FORECASTING JUMLAH KASUS PENDERITA PENYAKIT HIV / AIDS ( STUDI KASUS : KABUPATEN / KOTA DI PROVINSI SUMATERA SELATAN ). 9(4), 6531–6538.

Matematika, F., Alam, P., & Islam, U. (2021). Aplikasi metode box-jenkins (arima) untuk meramalkan harga komoditas cabai merah.

Matematika, J. I., & Roji, S. O. (2026).

MATH unesa. 14(01), 333–340.

No Title. (2024). 106–116.

Ode, L., Rakhman, A., Mustaqim, F., & Buton, U. M. (2026). SOSIALISASI EDUKASI PASAR MODAL SEBAGAI UPAYA. 5(01), 650–658.

Padjadjaran, U., Padjadjaran, U., & Padjadjaran, U. (2025). FORECASTING FERRY

PASSENGER TRAFFIC IN NEW YORK CITY USING. 7(3), 378–388.

Pratiwi, H., Nurhaliza, S. F., & Aprizkiyandari, S. (2024). Forecasting of Rubber Export Values in West Kalimantan Using the ARIMA Method. 3(2), 67–78.

Program, M. S. (2026). Forecast of Farmers’ Exchange Rate in Jambi Province Using The Arima Method ( Autoregressive Integrated Moving Average) Ti’ah Agustina 1* , Gusmanely. Z 2 1.2. 8(1), 182–195.

Rumpun, J., Dan, M., Jrme, E., Maret,

N., Janah, N. K., Dewi, I. K.,

Ekonomi, F., Pamulang, U., Selatan, T., Ekonomi, F., Pamulang, U., & Selatan, T.

(2026). Analisis Kebijakan Dividen Dan Nilai Perusahaan Terhadap Harga Saham Pada PT AKR Corporindo Tbk Tahun 2015-2024 dikenal dengan B-30 , sehingga total BBM dalam konsumsi energi final sekitar 36 % dan Grafik Oil Fuel Supply Demand BBM menunjukkan bahwa selama periode 2018- 2023 , Penjualan bahan bakar minyak ( BBM ) domestik pada tahun 2023 merupakan yang. 3(2).

Shidqi, M., Bariq, A., Sartono, B., & Sofia, A. (2025). IMPLEMENTATION OF THE GENERALIZED

AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY METHOD FOR FORECASTING THE STOCK RETURN OF PT LIPPO GENERAL INSURANCE TBK. 7(2), 123–134.

Triyawan, A., & Harris, A. Bin. (2023). Jakarta Islamic Index : Prediction With Autoregressive Integrated Moving Average Using R Studio. 5(2), 139–146.

Umar, U. T., & Barat, A. (2026). Open Access PENGARUH MODAL MINIMAL INVESTASI DAN MOTIVASI INVESTASI TERHADAP MINAT INVESTASI DI PASAR MODAL ( STUDI KASUS PADA MAHASISWA JURUSAN MANAJEMEN UNIVERSITAS TEUKU UMAR ) THE EFFECT OF MINIMUM CAPITAL INVESTMENT AND INVESTMENT ( A CASE STUDY ON MANAGEMENT STUDENTS AT TEUKU UMAR

Yulia Yusmi. 03(01).

Vidada, I. A., Erica, D., Universitas, F.

E. B., & Sarana, B. (2023). Analisis Perbandingan Fundamental Saham ICBP dan INDF. 1, 1–11.

Weldri, Y., Nanlohy, A., & Loklomin,

S. B. (2023). MODEL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) UNTUK MERAMALKAN INFLASI INDONESIA Autoregressive Integrated Moving Average (ARIMA) Model to Forecast Inflation In Indonesia. 5, 201