Green Suria Apartment

Apartment, Jln Green Suria, Tun Hussein Onn, 43200 Cheras, Selangor, Malaysia

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From
RM600K
Size
800 sqft

Property Transactions

6 subsales found

Median
RM368,000
PSF
RM360
Price Size
Period
transactions middle 50% (P25–P75)
RM370,000
Level 2
1,023 sqft RM362 PSF
RM380,000
Level 1
1,023 sqft RM372 PSF
RM366,000
Level 10
1,023 sqft RM358 PSF
RM370,000
Level 8
1,023 sqft RM362 PSF
RM350,000
Level 5
1,023 sqft RM342 PSF
RM348,000
Level 9
1,024 sqft RM340 PSF
Legend Recent Highest Price Highest PSF

Selling in Green Suria Apartment? Homes here sold for a median of RM368,000.

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Market Snapshot

Residential

RM368,000

RM360 psf

Median transaction price

Average

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Green Suria Apartment
© OpenStreetMap · CARTO

Apartment, Jln Green Suria, Tun Hussein Onn, 43200 Cheras, Selangor, Malaysia

Maps

Green Suria Apartment in Hulu Langat, Selangor recorded 6 subsale transactions between 2021 and 2026, sized between 975 and 1,024 sqft, with a median price of RM368K and a median price per square foot (PSF) of RM360.

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 RM368K, with most transactions falling within a stable range of RM357K to RM379K, and a typical market range of RM349K to RM380K.

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

For price per square foot, the median is RM360, with most transactions between RM349 and RM371. The usual range is RM336.76 to RM383.01, showing that most units are priced quite close to each other. A typical spread (IQR) of RM46.25 and an average deviation (MAD) of RM11 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.