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 (Lembaga Penelitian, Penerbitan dan Pengabdian Masyarakat Institut Agama Islam syarifuddin Lumajang, 2026)
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.