<![CDATA[Global economic developments and regional market dynamics significantly affect the performance of State-Owned Enterprises (BUMN). As an index that operates in the natural resources and energy sector, IDX-MES BUMN 17 is vulnerable to changes in global commodity prices. To address this challenge, two main approaches are used, namely fundamental analysis and technical analysis. In this study, the method used is Moving Average (MA) with lag MA(2) and MA(3), which was chosen to capture short-term price movement patterns. In addition, the simple exponential smoothing (SES) method with parameters 0.2 and 0.7 is also used to provide forecasts that are more responsive to changes in the latest data. Trend models such as linear, quadratic, exponential, and S-curve trends are applied to identify long-term trends of the macro and sectoral variables being analyzed. Seasonal forecasting methods such as Double Exponential Smoothing (DES) and the Winter method are used to model seasonal fluctuations that occur consistently. The results of the analysis conducted are IDX-MES BUMN 17 is divided into 2 clusters, cluster 1 selected ANTM and ELSA issuers, then in class 2 selected PTBA issuer. Of the three selected issuers, the highest return value is in the ANTM issuer, so the ANTM issuer is analyzed further. The best forecasting method for the three stocks is Double Exponential Smoothing. The results of the ANTM stock analysis show that the ANTM stock data is stationary, the ANTM stock also has cointegration in the short-term model to the long-term model and the three short-term models have met the IIDN assumptions]]>
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