Taman Universiti Indah

Seri Kembangan, Selangor, Malaysia

Property Transactions

3 subsales grouped by size

Median
RM 1,000,000
PSF
RM 315
Price Size
Period
transactions middle 50% (P25–P75)
3,200 sqft
Terrace Factory
RM 1,000,000
Jalan Indah 2/16
3,175 sqft · RM 315 PSF
RM 1,500,000
Jalan Indah 2/16
3,175 sqft · RM 472 PSF
RM 1,000,000
Jalan Indah 2/18
3,175 sqft · RM 315 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

RM 500,000

RM 447 psf

Median transaction price

RM 1,000,000

RM 315 psf

Median transaction price

Taman Universiti Indah
© OpenStreetMap · CARTO

Taman Universiti Indah, Seri Kembangan, Selangor, Malaysia

Maps

Taman Universiti Indah in Petaling, Selangor recorded 3 Terraced Factory properties subsale transactions between 2021 and 2026, with a median price of RM 1.00 million and a median price per square foot (PSF) of RM 315.

This area contains both residential and commercial properties. View 114 residential properties or 17 commercial properties separately for more focused analysis.

Price remained flat, and PSF growth was PSF remained flat. The median price is RM 1.00 million, with most transactions falling within a stable range of RM 1.00 million to RM 1.24 million, and a typical market range of RM 1.00 million to RM 1.15 million.

Within the Terraced Factory category, 2 - 2 1/2 storey terraced dominated the market, with high diversity across multiple property types.

Price per square foot shows a median of RM 315, though individual units vary from RM 241 to RM 389 in the core range. The broader market spans RM 221.93 to RM 407.93, indicating diverse property characteristics. The spread of RM 186.00 (IQR) and deviation of RM 74 (MAD) suggest moderate price variations reflecting different property features.

Overall, the market in this area appears stable with consistent appreciation, making it an attractive option for both investors and homebuyers. Moderate price stability provides a balanced market for both buyers and sellers. Limited transaction history suggests carefully evaluating comparable sales data.