Analisis Perbandingan Model ARIMA dan Exponential Smoothing dalam Meramalkan Harga Penutupan Saham - Abdul Aziz, Arif Rahman; Taqwa Prasetyaningrum, Putri (Building of Informatics, Technology and Science (BITS), 2025)
The stock market is one of the most sought-after investment instruments due to its high profit potential. However, significant fluctuations in stock prices also bring considerable risks, which are influenced by various factors such as macroeconomic conditions, government policies, company financial reports, and market sentiment. Therefore, stock price analysis and forecasting have become important aspects for investors and market participants in making more accurate investment decisions. This research focuses on the stock of PT Indosat Ooredoo Hutchison Tbk (ISAT), which shows high volatility, particularly following a sharp decline in stock prices in late February 2025, which was suspected to be triggered by discrepancies between financial reports and analysts' expectations.The main objective of this study is to compare two commonly used time series forecasting methods, namely Autoregressive Integrated Moving Average (ARIMA) and Exponential Smoothing, in predicting the closing price of ISAT stock. This research uses daily stock price data from October 28, 2022 to March 27, 2025, which is then analyzed to identify patterns in the movement of stock prices. Based on the analysis, it was found that both forecasting methods have their respective strengths and limitations. The ARIMA method is more accurate in handling stationary data, while Exponential Smoothing is more adaptive to fluctuating stock prices.The results of this study are expected to provide insights for investors in selecting the appropriate method to predict stock price movements with high volatility and help make smarter investment decisions as well as more effective risk management strategies.