Taman Merawan

Kedah, Kulim, Bandar Kulim

Property Transactions

16 subsales grouped by road

Period
transactions middle 50% (P25–P75)
RM280,000
990 sqft
RM283 PSF
RM265,000
990 sqft
RM268 PSF
RM275,000
990 sqft
RM278 PSF
RM270,000
990 sqft
RM273 PSF
RM350,000
1,862 sqft
RM188 PSF
RM225,000
990 sqft
RM227 PSF
RM200,000
990 sqft
RM202 PSF
RM500,000
2,906 sqft
RM172 PSF
RM600,000
5,985 sqft
RM100 PSF
RM300,000
2,454 sqft
RM122 PSF · Semi-D
RM440,000
2,400 sqft
RM183 PSF · Semi-D
RM350,000
2,271 sqft
RM154 PSF
RM620,000
2,400 sqft
RM258 PSF
RM550,000
2,400 sqft
RM229 PSF
RM330,000
2,239 sqft
RM147 PSF
RM500,000
3,380 sqft
RM148 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

Residential

RM350,000

RM227 psf

Median transaction price

Taman Merawan
© OpenStreetMap · CARTO

Taman Merawan, Kulim, Kedah

Taman Merawan in Kulim, Kedah recorded 16 subsale transactions between 2021 and 2026, with a median price of RM340K and a median price per square foot (PSF) of RM202.

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 RM340K, with most transactions falling within a stable range of RM253K to RM428K, and a typical market range of RM227K to RM453K.

Most transactions involved low-cost house, with high diversity across multiple property types.

Price per square foot shows a median of RM202, though individual units vary from RM154 to RM249 in the core range. The broader market spans RM147.96 to RM255.96, indicating diverse property characteristics. The spread of RM108.00 (IQR) and deviation of RM48 (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.