Taman Desa Impian/Sri Orkid

Kedah, Kulim, Bandar Kulim

Property Transactions

16 subsales grouped by road

Period
transactions middle 50% (P25–P75)
RM330,000
2,465 sqft
RM134 PSF
RM238,000
1,313 sqft
RM181 PSF
RM210,000
1,324 sqft
RM159 PSF
RM215,000
1,259 sqft
RM171 PSF
RM230,000
1,313 sqft
RM175 PSF
RM450,000
1,442 sqft
RM312 PSF
RM310,000
1,442 sqft
RM215 PSF
RM340,000
2,788 sqft
RM122 PSF
RM428,000
1,442 sqft
RM297 PSF
RM250,000
1,324 sqft
RM189 PSF
RM280,000
1,507 sqft
RM186 PSF
RM420,000
3,595 sqft
RM117 PSF
RM295,000
2,422 sqft
RM122 PSF
RM420,000
3,595 sqft
RM117 PSF
RM500,000
6,695 sqft
RM75 PSF
RM260,000
2,325 sqft
RM112 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

Residential

RM260,000

RM171 psf

Median transaction price

Taman Desa Impian/Sri Orkid in Kulim, Kedah recorded 16 subsale transactions between 2021 and 2026, with a median price of RM303K and a median price per square foot (PSF) of RM171.

This area contains both residential and commercial properties. View 11 residential properties or 1 commercial properties separately for more focused analysis.

Price remained flat, and PSF growth was PSF remained flat. The median price is RM303K, with most transactions falling within a stable range of RM234K to RM371K, and a typical market range of RM216K to RM389K.

Most transactions involved 1 - 1 1/2 storey terraced, with high diversity across multiple property types.

The median PSF stands at RM171, with core pricing between RM139 and RM203. Market pricing typically extends from RM139.60 to RM201.85, reflecting moderate variation in unit pricing. The spread of RM62.25 (IQR) and deviation of RM32 (MAD) suggest moderate price variations reflecting different property features.

While the area has shown positive growth trends, price variations suggest a more dynamic market. This presents opportunities for investors comfortable with moderate volatility. Some price volatility exists, making thorough market research essential before transacting. Limited transaction history suggests carefully evaluating comparable sales data.