Maisson @ Platinum Apartment

Maisson, Ara Damansara, 47301 Petaling Jaya, Selangor, Malaysia

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From
RM 600K
Size
800 sqft

Property Transactions

8 subsales grouped by size

Median
RM 427,500
PSF
RM 577
Price Size
Period
transactions middle 50% (P25–P75)
500 sqft
Serviced Apt
RM 300,000
Level 9
495 sqft · RM 606 PSF
RM 290,000
Level 4
495 sqft · RM 586 PSF
600 sqft
Serviced Apt
RM 440,000
Level 6
603 sqft · RM 730 PSF
700 sqft
Serviced Apt
RM 385,000
Level 10
678 sqft · RM 568 PSF
RM 415,000
Level 10
678 sqft · RM 612 PSF
1,000 sqft
Serviced Apt
RM 563,000
Level 13
1,023 sqft · RM 551 PSF
1,400 sqft
Serviced Apt
RM 755,000
Level 20
1,378 sqft · RM 548 PSF
RM 735,000
Level 22
1,378 sqft · RM 533 PSF
Legend Recent Highest Price Highest PSF

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Maisson @ Platinum Apartment
© OpenStreetMap · CARTO

Maisson, Ara Damansara, 47301 Petaling Jaya, Selangor, Malaysia

Maps

Maisson @ Platinum Apartment in Petaling, Selangor recorded 8 subsale transactions in 2025, with a median price of RM 428K and a median price per square foot (PSF) of RM 577.

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 428K, with most transactions falling within a stable range of RM 290K to RM 597K, and a typical market range of RM 347K to RM 508K.

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

The median PSF stands at RM 577, with core pricing between RM 518 and RM 635. Market pricing typically extends from RM 532.97 to RM 620.47, reflecting moderate variation in unit pricing. With an IQR of RM 87.50 and MAD of RM 58, 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.