Taman Desa Impian/Sri Orkid

Kedah, Kulim, Bandar Kulim

Property Transactions

6 subsales grouped by size

Median
RM 340,000
PSF
RM 138
Price Size
Period
transactions middle 50% (P25–P75)
1,300 sqft
Terrace
RM 238,000
Lorong. Kenanga 3B
1,313 sqft · RM 181 PSF
RM 210,000
Lorong. Kenanga 3B
1,324 sqft · RM 159 PSF
1,450 sqft
2-Sty Terrace
RM 450,000
Lorong. Kenanga 3
1,442 sqft · RM 312 PSF
2,350 sqft
Terrace
RM 260,000
Lorong Kenanga 3B
2,325 sqft · RM 112 PSF
3,600 sqft
Semi-D
RM 420,000
Lorong. Kenanga 4
3,595 sqft · RM 117 PSF
6,700 sqft
Semi-D
RM 500,000
Lorong Kenanga 4
6,695 sqft · RM 75 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

Residential

RM 340,000

RM 138 psf

Median transaction price

Taman Desa Impian/Sri Orkid in Kulim, Kedah recorded 6 subsale transactions in 2022, with a median price of RM 340K and a median price per square foot (PSF) of RM 138.

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 RM 340K, with most transactions falling within a stable range of RM 226K to RM 454K, and a typical market range of RM 254K to RM 427K.

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

Price per square foot shows a median of RM 138, though individual units vary from RM 61 to RM 214 in the core range. The broader market spans RM 106.60 to RM 168.85, indicating diverse property characteristics. A wider spread (IQR: RM 62.25) and deviation (MAD: RM 76) indicate significant PSF variations, likely due to diverse property types or conditions.

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.