Sucasa Apt

222, Jln Ampang, Kampung Datuk Keramat, 55000 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia

Property Transactions

4 subsales grouped by size

Median
RM400,000
PSF
RM570
Period
transactions middle 50% (P25–P75)
600 sqft
Condo
RM350,000
Level 10
614 sqft · RM570 PSF
650 sqft
Condo
RM350,000
Level 6
646 sqft · RM542 PSF
800 sqft
Condo
RM460,000
Level 5
797 sqft · RM578 PSF
1,000 sqft
Condo
RM450,000
Level 18
990 sqft · RM454 PSF
Legend Recent Highest Price Highest PSF

Selling in Sucasa Apt? Homes here sold for a median of RM400,000.

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222, Jln Ampang, Kampung Datuk Keramat, 55000 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia

Maps

Sucasa Apt in Kuala Lumpur recorded 4 subsale transactions between 2021 and 2026, with a median price of RM400K and a median price per square foot (PSF) of RM570.

Nothing is listed in Sucasa Apt right now. Browse properties for sale in Kuala Lumpur Town Centre and properties for rent in Kuala Lumpur Town Centre nearby, then use the 4 sales recorded here to judge whether an asking price is fair.

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 RM400K, with most transactions falling within a stable range of RM350K to RM450K, and a typical market range of RM350K to RM451K.

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

For price per square foot, the median is RM570, with most transactions between RM552 and RM588. The usual range is RM544.46 to RM596.46, showing that most units are priced quite close to each other. With an IQR of RM52.00 and MAD of RM18, the PSF demonstrates reasonable consistency across the market.

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.