Kampung Baru Sungai Buloh

40160 Sungai Buloh, Selangor, Malaysia

Property Transactions

5 subsales grouped by size

Period
transactions middle 50% (P25–P75)
1,000 sqft
LC House
RM150,000
Rum Mur.rc.kilat
1,000 sqft · RM150 PSF
RM150,000
Rancangan Rumah Kilat
1,000 sqft · RM150 PSF
6,250 sqft
Bungalow
RM720,000
Jalan Love Lane
6,261 sqft · RM115 PSF
7,350 sqft
Bungalow
RM880,000
Jalan Citizen Avenue
7,358 sqft · RM120 PSF
7,600 sqft
Bungalow
RM950,000
Jalan Union
7,623 sqft · RM125 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

Residential

RM720,000

RM125 psf

Median transaction price

Low

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Gross yield, median rent and sale psf — worked out from transacted prices and asking rents.

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Kampung Baru Sungai Buloh
© OpenStreetMap · CARTO

Kampung Baru Sungai Buloh, 40160 Sungai Buloh, Selangor, Malaysia

Maps

Kampung Baru Sungai Buloh in Petaling, Selangor recorded 5 subsale transactions between 2021 and 2026, with a median price of RM720K and a median price per square foot (PSF) of RM125.

This area consists exclusively of residential properties, with no commercial listings recorded.

Price remained flat, and PSF growth was PSF remained flat. The median price is RM720K, with most transactions falling within a stable range of RM490K to RM950K, and a typical market range of RM355K to RM950K.

Most transactions involved detached, though some variety exists in the market.

For price per square foot, the median is RM125, with most transactions between RM115 and RM135. The usual range is RM109.62 to RM139.62, showing that most units are priced quite close to each other. A typical spread (IQR) of RM30.00 and an average deviation (MAD) of RM10 indicate a highly stable PSF trend across properties.

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.