Taman Ria Vistana

Jln Ria Vistana, Taman Ria Vistana, 09400 Padang Serai, Kedah, Malaysia

Property Transactions

3 subsales grouped by size

Median
RM 407,000
PSF
RM 200
Price Size
Period
transactions middle 50% (P25–P75)
1,300 sqft
LC House
RM 260,000
Taman Ria Vistana
1,300 sqft · RM 200 PSF
2,300 sqft
Terrace Factory
RM 628,000
Taman Ria Vistana
2,282 sqft · RM 275 PSF
2,800 sqft
Semi-D
RM 407,000
Jalan Ria Vistana 7
2,800 sqft · RM 145 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

RM 333,500

RM 173 psf

Median transaction price

RM 628,000

RM 275 psf

Median transaction price

Taman Ria Vistana
© OpenStreetMap · CARTO

Jln Ria Vistana, Taman Ria Vistana, 09400 Padang Serai, Kedah, Malaysia

Maps

Taman Ria Vistana in Kulim, Kedah recorded 3 subsale transactions between 2021 and 2026, with a median price of RM 407K and a median price per square foot (PSF) of RM 200.

This area contains both residential and commercial properties. View 31 residential properties or 12 commercial properties separately for more focused analysis.

Price remained flat, and PSF growth was PSF remained flat. The median price is RM 407K, with most transactions falling within a stable range of RM 260K to RM 558K, and a typical market range of RM 291K to RM 523K.

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

Price per square foot shows a median of RM 200, though individual units vary from RM 147 to RM 253 in the core range. The broader market spans RM 174.46 to RM 225.46, indicating diverse property characteristics. A wider spread (IQR: RM 51.00) and deviation (MAD: RM 53) 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.