Wangsa Melawati

Lorong Penghulu, Gombak Setia, 53100 Kuala Lumpur, Selangor, Malaysia

Property Transactions

2 subsales grouped by size

Median
RM2,350,000
PSF
RM511
Price Size
Period
transactions middle 50% (P25–P75)
4,600 sqft
4-Sty Shop
RM2,600,000
Jalan Wangsa Setia 1
4,596 sqft · RM566 PSF
RM2,100,000
Jalan Wira Setia 3
4,596 sqft · RM457 PSF
Legend Recent Highest Price Highest PSF

Selling in Wangsa Melawati? Homes here sold for a median of RM2,350,000.

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Market Snapshot

RM630,000

RM582 psf

Median transaction price

RM2,350,000

RM511 psf

Median transaction price

Wangsa Melawati
© OpenStreetMap · CARTO

Lorong Penghulu, Gombak Setia, 53100 Kuala Lumpur, Selangor, Malaysia

Maps

Wangsa Melawati in Kuala Lumpur, Kuala Lumpur recorded 2 4-Storey Shop properties subsale transactions between 2021 and 2026, with a median price of RM2.35 million and a median price per square foot (PSF) of RM511.

This area contains both residential and commercial properties. View 42 residential properties or 8 commercial properties separately for more focused analysis.

Price remained flat, and PSF growth was PSF remained flat. The median price is RM2.35 million, with most transactions falling within a stable range of RM2.10 million to RM2.60 million, and a typical market range of RM2.14 million to RM2.56 million.

Within the 4-Storey Shop category, 2 - 2 1/2 storey terraced dominated the market, with moderate diversity in property types available.

The median PSF stands at RM511, with core pricing between RM457 and RM566. Market pricing typically extends from RM432.92 to RM589.67, reflecting moderate variation in unit pricing. With an IQR of RM156.75 and MAD of RM54, 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. Despite diverse property types, prices remain relatively stable, offering options for different buyer preferences. Limited transaction history suggests carefully evaluating comparable sales data.