Taman Perkasa

Butterworth, Pulau Pinang, Malaysia

Property Transactions

5 subsales grouped by size

Price Size
Period
transactions middle 50% (P25–P75)
2,200 sqft
Semi-D
RM840,000
Lorong Perkasa 11
2,207 sqft · RM381 PSF
2,450 sqft
Semi-D
RM840,000
Lorong Perkasa 11
2,443 sqft · RM344 PSF
2,550 sqft
Semi-D
RM860,000
Lorong Perkasa 1
2,551 sqft · RM337 PSF
2,850 sqft
Semi-D
RM850,000
Lorong Perkasa 1
2,863 sqft · RM297 PSF
3,000 sqft
Semi-D
RM885,000
Lorong Perkasa 11
2,992 sqft · RM296 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

Residential

RM850,000

RM337 psf

Median transaction price

Taman Perkasa
© OpenStreetMap · CARTO

Taman Perkasa, Butterworth, Pulau Pinang, Malaysia

Maps

Taman Perkasa in Seberang Perai Utara, Penang recorded 5 Double Storey Semi-D properties subsale transactions between 2021 and 2026, with a median price of RM850K and a median price per square foot (PSF) of RM337.

This area contains both residential and commercial properties. View 15 residential properties or 4 commercial properties separately for more focused analysis.

Price remained flat, and PSF growth was PSF remained flat. The median price is RM850K, with most transactions falling within a stable range of RM840K to RM867K, and a typical market range of RM840K to RM885K.

Within the Double Storey Semi-D category, 2 - 2 1/2 storey terraced dominated the market, with high diversity across multiple property types.

For price per square foot, the median is RM337, with most transactions between RM305 and RM369. The usual range is RM246.12 to RM428.12, showing that most units are priced quite close to each other. With an IQR of RM182.00 and MAD of RM32, 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.