Dynamic Mapping of Financial Performance and Valuation Profiles among Indonesian Listed Construction Companies Using K-Means Clustering

Abstract

The construction sector plays an important role in Indonesia’s economic development; however, construction companies face various financial challenges, including profitability pressures, high leverage levels, and fluctuating market valuations. A comprehensive assessment of financial performance and valuation profiles is needed to identify company conditions and support potential acquisition screening. This study aimed to map changes in the financial performance and valuation profiles of construction companies listed on the Indonesia Stock Exchange during 2024–2025 using a clustering approach. A quantitative descriptive-exploratory method was applied using secondary data obtained from financial statements and market-based ratios. The sample consisted of 24 construction companies with 48 company-year observations. The analysis employed K-Means Clustering supported by data preprocessing, Principal Component Analysis (PCA), and cluster evaluation based on statistical validity and economic interpretation. The findings revealed three distinct profiles: companies with strong profitability and moderate valuation, companies with low leverage but weak earnings performance, and companies with high leverage and financial losses. The migration analysis showed that 18 companies remained in the same profile, while six companies shifted toward weaker financial conditions. These findings indicate that financial performance and valuation mapping through clustering can provide an objective initial screening framework for investors, management, and stakeholders in evaluating company risks and strategic opportunities. Future studies are recommended to incorporate additional indicators, such as cash flow, liquidity, and market risk, to improve assessment accuracy.