Ritze Perdana

Damansara Perdana, 47820 Petaling Jaya, Selangor, Malaysia

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From
RM600K
Size
800 sqft

Property Transactions

12 subsales grouped by size

Median
RM212,500
PSF
RM556
Price Size
Period
transactions middle 50% (P25–P75)
400 sqft
Serviced Apt
RM215,000
Level 9
382 sqft · RM563 PSF
RM235,000
Level 9
382 sqft · RM615 PSF
RM188,000
Level 3A
382 sqft · RM492 PSF
RM250,000
Level 3
406 sqft · RM616 PSF
RM230,000
Level 1
409 sqft · RM562 PSF
RM205,000
Level 9
406 sqft · RM505 PSF
+5 more
1,000 sqft
Serviced Apt
RM1,200,000
Level G
1,001 sqft · RM1,199 PSF
Legend Recent Highest Price Highest PSF

Selling in Ritze Perdana? Homes here sold for a median of RM212,500.

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Ritze Perdana Service Apt
© OpenStreetMap · CARTO

Ritze Perdana, Damansara Perdana, 47820 Petaling Jaya, Selangor, Malaysia

Maps

Ritze Perdana in Petaling, Selangor recorded 12 subsale transactions between 2021 and 2026, with a median price of RM213K and a median price per square foot (PSF) of RM556.

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 RM213K, with most transactions falling within a stable range of RM185K to RM486K, and a typical market range of RM185K to RM248K.

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

Price per square foot shows a median of RM556, though individual units vary from RM367 to RM745 in the core range. The broader market spans RM513.34 to RM598.84, indicating diverse property characteristics. A wider spread (IQR: RM85.50) and deviation (MAD: RM189) 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.