PT Kian Santang Muliatama Tbk (RGAS) Fair Value & Analysis
Energy · ID · Market cap 153B IDR
Fair value as of: Jun 24, 2026
Analysis
PT Kian Santang Muliatama Tbk (RGAS) currently trades at 181.00 IDR, while our model-based Fair Value estimate is 254.09 IDR — implying the stock looks roughly 40.4% undervalued today. We read business quality at 85/100 (high quality), in the Energy 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 Kian Santang Muliatama Tbk engages in the supply of spare parts to gas industry in Indonesia. It operates in two segments, Trading, and Constructions Service and Others. It offers gas meters, converter kits, regulators, transition fitting, meter regulating stations, and regulating stations under the RMG, Tormene, Canalta, Honeywell, Dunyun, Ergas, Sejin Valve, and Rucika brands. The company also provides supporting services to the gas industry; and engineering, procurement, and construction services, including design and engineering, site installation, and testing and commissioning services, as well as infrastructure and fabrication works. In addition, it engages in the architectural and engineering, technical analysis and testing, human health, and certification, oil and gas installation, and laboratory testing services; and manufacturing industry, including plastic pipes, special metalworking services and metal goods, manual measuring and testing equipment, pumps, general machi…
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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.