Taman Desa Moccis

Desa Moccis, Shah Alam, Selangor, Malaysia

Property Transactions

3 subsales grouped by size

Period
transactions middle 50% (P25–P75)
3,200 sqft
Semi-D
RM600,000
Jalan Dm 2
3,197 sqft · RM188 PSF
4,000 sqft
Bungalow
RM500,000
Jalan Dm 3
4,004 sqft · RM125 PSF
4,150 sqft
Bungalow
RM750,000
Jalan Dm 3
4,133 sqft · RM181 PSF
Legend Recent Highest Price Highest PSF

Selling in Taman Desa Moccis? Homes here sold for a median of RM600,000.

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

List your property free

New Launches in Selangor

View all

Posts about Taman Desa Moccis

What’s happening in Taman Desa Moccis?

No posts about Taman Desa Moccis yet. Be the first to share what’s happening here.

Property News

More property news →
Taman Desa Moccis
© OpenStreetMap · CARTO

Desa Moccis, Shah Alam, Selangor, Malaysia

Maps

Taman Desa Moccis in Petaling, Selangor recorded 3 subsale transactions between 2021 and 2026, with a median price of RM600K and a median price per square foot (PSF) of RM181.

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 RM600K, with most transactions falling within a stable range of RM500K to RM700K, and a typical market range of RM538K to RM663K.

Most transactions involved detached, though some variety exists in the market.

For price per square foot, the median is RM181, with most transactions between RM174 and RM188. The usual range is RM165.70 to RM197.20, showing that most units are priced quite close to each other. A typical spread (IQR) of RM31.50 and an average deviation (MAD) of RM7 indicate a highly stable PSF trend across properties.

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.