Bandar Sri Mahkota

Kedah, Kulim, Bandar Kulim

Property Transactions

13 subsales grouped by size

Price Size
Period
transactions middle 50% (P25–P75)
1,200 sqft
LC House
RM210,000
Lorong Mahkota 21/2
1,195 sqft · RM176 PSF
RM290,000
Lorong. Mahkota 15/2
1,302 sqft · RM223 PSF
RM306,000
Lorong. Mahkota 15/2
1,302 sqft · RM235 PSF
RM230,000
Lorong Mahkota 29/2
1,302 sqft · RM177 PSF
RM250,000
Lorong Mahkota 24/2
1,302 sqft · RM192 PSF
RM270,000
Lorong Mahkota 24/2
1,302 sqft · RM207 PSF
RM295,000
Lorong Mahkota 17/2
1,302 sqft · RM226 PSF
+4 more
1,650 sqft
Terrace
RM330,000
Lorong Mahkota 9/2
1,647 sqft · RM200 PSF
1,800 sqft
Terrace
RM280,000
Lorong Mahkota 15/2
1,808 sqft · RM155 PSF
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Market Snapshot

Residential

RM290,000

RM211 psf

Median transaction price

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Bandar Sri Mahkota, Kulim, Kedah

Bandar Sri Mahkota in Kulim, Kedah recorded 13 subsale transactions between 2021 and 2026, with a median price of RM290K and a median price per square foot (PSF) of RM211.

This area contains both residential and commercial properties. View 45 residential properties or 2 commercial properties separately for more focused analysis.

Price remained flat, and PSF growth was PSF remained flat. The median price is RM290K, with most transactions falling within a stable range of RM254K to RM326K, and a typical market range of RM255K to RM325K.

Most transactions involved low-cost house, with moderate diversity in property types available.

The median PSF stands at RM211, with core pricing between RM182 and RM240. Market pricing typically extends from RM189.14 to RM233.14, reflecting moderate variation in unit pricing. With an IQR of RM44.00 and MAD of RM29, the PSF demonstrates reasonable consistency across the market.

Overall, the market in this area appears stable with consistent appreciation, making it an attractive option for both investors and homebuyers. Despite diverse property types, prices remain relatively stable, offering options for different buyer preferences. Limited transaction history suggests carefully evaluating comparable sales data.