Lestari Apartment

Jalan Tasik Permaisuri 3, Bandar Sri Permaisuri, Cheras, Bandar Sri Permaisuri, 56000 Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia

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From
RM600K
Size
800 sqft

Property Transactions

3 subsales grouped by size

Median
RM330,000
PSF
RM403
Price Size
Period
transactions middle 50% (P25–P75)
800 sqft
Condo
RM288,000
Level 8
818 sqft · RM352 PSF
RM400,000
Level 12
818 sqft · RM489 PSF
RM330,000
Level 10
818 sqft · RM403 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

Residential

RM330,000

RM403 psf

Median transaction price

High

Does LESTARI APARTMENT rent out well?

Gross yield, median rent and sale psf — worked out from transacted prices and asking rents.

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Lestari Apartment
© OpenStreetMap · CARTO

Jalan Tasik Permaisuri 3, Bandar Sri Permaisuri, Cheras, Bandar Sri Permaisuri, 56000 Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia

Maps

Lestari Apartment in Kuala Lumpur, Kuala Lumpur recorded 3 subsale transactions in 2024, with a median price of RM330K and a median price per square foot (PSF) of RM403.

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 RM330K, with most transactions falling within a stable range of RM288K to RM376K, and a typical market range of RM300K to RM360K.

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

The median PSF stands at RM403, with core pricing between RM347 and RM460. Market pricing typically extends from RM366.39 to RM440.39, reflecting moderate variation in unit pricing. With an IQR of RM74.00 and MAD of RM56, 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.