Pangsapuri Sri Kerjaya Apartment

Hicom-glenmarie Industrial Park, 40150 Shah Alam, Selangor, Malaysia

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From
RM 600K
Size
800 sqft

Property Transactions

12 subsales grouped by size

Median
RM 272,500
PSF
RM 323
850 sqft
Condo
RM 280,000
Level G
855 sqft · RM 327 PSF
900 sqft
Condo
RM 300,000
Level 3
893 sqft · RM 336 PSF
RM 270,000
Level 1
893 sqft · RM 302 PSF
RM 250,000
Level 4
893 sqft · RM 280 PSF
RM 308,000
Level 2
893 sqft · RM 345 PSF
RM 275,000
Level 3
893 sqft · RM 308 PSF
RM 250,000
Level 2
883 sqft · RM 283 PSF
+5 more
Legend Recent Highest Price Highest PSF

Market Snapshot

Residential

RM 272,500

RM 305 psf

Median transaction price

Sri Kerjaya Apartment-U1 Glenmarie
© OpenStreetMap · CARTO

Pangsapuri Sri Kerjaya Apartment, Hicom-glenmarie Industrial Park, 40150 Shah Alam, Selangor, Malaysia

Maps

Pangsapuri Sri Kerjaya Apartment in Petaling, Selangor recorded 12 subsale transactions between 2021 and 2026, with a median price of RM 273K and a median price per square foot (PSF) of RM 323.

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 RM 273K, with most transactions falling within a stable range of RM 250K to RM 295K, and a typical market range of RM 255K to RM 290K.

Most transactions involved condominium/apartment, with minimal variety in property types.

For price per square foot, the median is RM 323, with most transactions between RM 301 and RM 345. The usual range is RM 301.27 to RM 344.52, showing that most units are priced quite close to each other. A typical spread (IQR) of RM 43.25 and an average deviation (MAD) of RM 22 indicate a highly stable PSF trend across properties.

Overall, the market in this area appears stable with consistent appreciation, making it an attractive option for both investors and homebuyers. The consistent property type and stable pricing make it easier to assess value and compare trends. Limited transaction history suggests carefully evaluating comparable sales data.