Wangsa Melawati

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

Property Transactions

1 subsales grouped by size

Price Size
Period
transactions middle 50% (P25–P75)
1,100 sqft
LC House
RM700,000
Wangsa Budi 5B
1,076 sqft · RM650 PSF
Legend Recent Highest Price Highest PSF

Selling in Wangsa Melawati? Homes here sold for a median of RM700,000.

Free to list, about two minutes, and the buyers reading this page will see it.

List your property free

Posts about Wangsa Melawati

What’s happening in Wangsa Melawati?

No posts about Wangsa Melawati yet. Be the first to share what’s happening here.

Market Snapshot

RM700,000

RM650 psf

Median transaction price

RM1,650,000

RM1,294 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 1 Low-Cost House properties subsale transactions between 2021 and 2026, with a median price of RM700K and a median price per square foot (PSF) of RM650.

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.

Within the Low-Cost House category, 2 - 2 1/2 storey terraced dominated the market, with moderate diversity in property types available.

For price per square foot, the median is RM650, with most transactions between RM650 and RM650. The usual range is RM571.95 to RM728.70, showing that most units are priced quite close to each other. With an IQR of RM156.75 and MAD of RM0, 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. Significant price variations suggest comparing multiple properties and timing the market carefully. Limited transaction history suggests carefully evaluating comparable sales data.