PT Global Sukses Solusi Tbk (RUNS) Fair Value & Analysis
Technology · ID · Market cap 66.7B IDR
Fair value as of: Jun 24, 2026
Analysis
PT Global Sukses Solusi Tbk (RUNS) currently trades at 76.00 IDR, while our model-based Fair Value estimate is 93.23 IDR — implying the stock looks roughly 22.7% undervalued today. We read business quality at 88/100 (high quality), in the Technology sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: medium) — always confirm before acting.
About the company
PT Global Sukses Solusi Tbk provides enterprise resource planning software solutions under the RUN System brand name for various business processes in Southeast Asia. The company provides various solutions for cost control, cash flow management, asset management, enterprise accounting, account payable, and account receivable; sales management, international trade logistics, and distribution management; and purchasing management, contract management, raw material purchasing, and e-procurement. It also offers material management, warehouse management system, and inventory management; production management, production planning, capacity planning, and material requirement planning; and performance, organization, assessment, training, and recruitment management services. In addition, the company provides custom application development, professional, and information technology services. It serves the manufacturing, construction, mining and quarrying, financial services, agriculture and fo…
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.