CLASSIFICATION ANALYSIS USING MINIMUM SPANNING TREE AND PREDICTIONS USING ARIMA ON THE MOST INFLUENTIAL STOCKS ON THE LQ45 INDEX - Theo Markus; Ayu Sofia; Dwi Mahrani (Jurnal Statistika dan Aplikasinya, 2025)
The 2023 recession, largely driven by high inflation, highlights the importance of investing. The stock market, with its regulated framework and potential for significant returns, presents a viable investment option. The LQ45, an index tracking the top 45 Indonesian stocks by market capitalization, provides a benchmark. To identify promising investments, this study employed the Minimum Spanning Tree (MST) method to pinpoint the most influential stocks within the LQ45 network, followed by Auto-Regressive Integrated Moving Average (ARIMA) for price prediction. The MST analysis, utilizing degree centrality, closeness, and betweenness measures, identified BBNI as the most influential, followed by BBTN and BMRI. Price predictions for BBNI and BBTN exhibited close alignment with actual market prices, while BMRI showed a larger deviation. For BBNI shares, the ARIMA(1,0,0) model is used with a MAPE of 1.78%; for BBTN shares, the ARIMA(0,2,2) model is used with a MAPE of 2.65%; and for BMRI shares, the ARIMA(2,2,1) model is used with a MAPE of 1.84%. This research contributes to the field of stock market analysis by demonstrating the effectiveness of combining network analysis techniques, specifically the MST method, with time series forecasting models like ARIMA for stock selection. The findings provide valuable insights for investors seeking to navigate market volatility and make informed investment decisions. The findings of this research can serve as a valuable guide for investors considering BBNI, BBTN, and BMRI shares.