Bukit Jelutong

Shah Alam, Selangor, Malaysia

Property Transactions

5 subsales grouped by size · Semi-D Factory →

Median
RM 7,450,000
PSF
RM 475
Price Size
Period
transactions middle 50% (P25–P75)
8,900 sqft
Semi-D Factory
RM 4,170,000
Jalan Astaka U8/88A
8,883 sqft · RM 469 PSF
8,950 sqft
Semi-D Factory
RM 4,470,000
Jalan Astaka U8/88B
8,928 sqft · RM 501 PSF
12,600 sqft
Semi-D Factory
RM 7,450,000
Jalan Para U8/103
12,600 sqft · RM 591 PSF
16,000 sqft
Semi-D Factory
RM 7,600,000
Jalan Para U8/103
15,996 sqft · RM 475 PSF
16,950 sqft
Semi-D Factory
RM 7,650,000
Jalan Astaka U8/82
16,953 sqft · RM 451 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

Commercial

RM 7,450,000

RM 475 psf

Median transaction price

High

Rental Yield Data

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Bukit Jelutong, Shah Alam, Selangor, Malaysia

Maps

Bukit Jelutong in Petaling, Selangor recorded 5 subsale transactions in 2023, with a median price of RM 7.45 million and a median price per square foot (PSF) of RM 475.

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

Price remained flat, and PSF growth was PSF remained flat. The median price is RM 7.45 million, with most transactions falling within a stable range of RM 5.86 million to RM 7.65 million, and a typical market range of RM 6.03 million to RM 7.65 million.

Most transactions involved semi-detached factory/warehouse, though some variety exists in the market.

The median PSF stands at RM 475, with core pricing between RM 426 and RM 525. Market pricing typically extends from RM 405.11 to RM 545.11, reflecting moderate variation in unit pricing. With an IQR of RM 140.00 and MAD of RM 49, the PSF demonstrates reasonable consistency across the market.

While the area has shown positive growth trends, price variations suggest a more dynamic market. This presents opportunities for investors comfortable with moderate volatility. Some price volatility exists, making thorough market research essential before transacting. Limited transaction history suggests carefully evaluating comparable sales data.