| Road | Price | PSF | Size | Date | Type |
|---|
|
Jalan Qamari U5/107B
|
RM 565,000
|
RM 404
|
1,399 sqft
|
|
|
Jalan Qamari U5/107B
|
RM 645,000
|
RM 370
|
1,744 sqft
|
|
|
|
Jalan Qamari U5/107A
|
RM 560,000
|
RM 321
|
1,744 sqft
|
|
|
|
Jalan Qamari U5/107C
|
RM 750,000
|
RM 430
|
1,744 sqft
|
|
|
Jalan Qamari U5/109
|
RM 650,000
|
RM 362
|
1,798 sqft
|
|
|
Jalan Qamari U5/112
|
RM 540,000
|
RM 270
|
2,002 sqft
|
|
|
|
Jalan Qamari U5/110
|
RM 615,000
|
RM 307
|
2,002 sqft
|
|
|
Jalan Qamari U5/108
|
RM 720,000
|
RM 295
|
2,443 sqft
|
|
Posts about Taman Nusa Subang
No posts about Taman Nusa Subang yet. Be the first to share what’s happening here.
Property News
More property news →Promote your property to visitors of this page
Market Snapshot
ResidentialRM 630,000
RM 341 psfMedian transaction price
Taman Nusa Subang, 40150 Shah Alam, Selangor, Malaysia
MapsTaman Nusa Subang in Petaling, Selangor recorded 8 subsale transactions in 2024, with a median price of RM 630K and a median price per square foot (PSF) of RM 341.
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 RM 630K, with most transactions falling within a stable range of RM 559K to RM 701K, and a typical market range of RM 583K to RM 678K.
Most transactions involved 2 - 2 1/2 storey terraced, with minimal variety in property types.
The median PSF stands at RM 341, with core pricing between RM 289 and RM 394. Market pricing typically extends from RM 312.87 to RM 369.87, reflecting moderate variation in unit pricing. The spread of RM 57.00 (IQR) and deviation of RM 52 (MAD) suggest moderate price variations reflecting different property features.
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.