Taman Bukit Rahman Putra

Bukit Rahman Putra, 47000 Sungai Buloh, Selangor, Malaysia

Property Transactions

3 subsales grouped by size

Median
RM 180,000
PSF
RM 115
Price Size
Period
transactions middle 50% (P25–P75)
1,450 sqft
Office
RM 350,000
Level 3
1,464 sqft · RM 239 PSF
1,550 sqft
Office
RM 180,000
Level 3
1,560 sqft · RM 115 PSF
RM 160,000
Level 2
1,560 sqft · RM 103 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

RM 925,000

RM 423 psf

Median transaction price

RM 180,000

RM 115 psf

Median transaction price

Taman Bukit Rahman Putra
© OpenStreetMap · CARTO

Bukit Rahman Putra, 47000 Sungai Buloh, Selangor, Malaysia

Maps

Taman Bukit Rahman Putra in Petaling, Selangor recorded 3 Office Lot properties subsale transactions between 2021 and 2026, with a median price of RM 180K and a median price per square foot (PSF) of RM 115.

This area contains both residential and commercial properties. View 66 residential properties or 23 commercial properties separately for more focused analysis.

Price remained flat, and PSF growth was PSF remained flat. The median price is RM 180K, with most transactions falling within a stable range of RM 160K to RM 265K, and a typical market range of RM 160K to RM 350K.

Within the Office Lot 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 115, though individual units vary from RM 54 to RM 177 in the core range. The broader market spans RM 0.00 to RM 237.88, indicating diverse property characteristics. A wider spread (IQR: RM 245.00) and deviation (MAD: RM 62) indicate significant PSF variations, likely due to diverse property types or conditions.

While the area has shown positive growth trends, price variations suggest a more dynamic market. This presents opportunities for investors comfortable with moderate volatility. Significant price variations suggest comparing multiple properties and timing the market carefully. Limited transaction history suggests carefully evaluating comparable sales data.