Pengkalan Maju Industrial Park

Perak, Kinta, Ulu Kinta

Property Transactions

7 subsales grouped by size

Price Size
Period
transactions middle 50% (P25–P75)
3,000 sqft
Terrace Factory
RM260,000
Psrn Kilang Pengkalan 22
3,014 sqft · RM86 PSF
RM310,000
Persiaran Perindustrian Pengkalan 22
3,014 sqft · RM103 PSF
RM325,000
Prsn Kilang Pengkalan 26
3,014 sqft · RM108 PSF
RM310,000
Persiaran Perindustrian Pengkalan 22
3,014 sqft · RM103 PSF
RM260,000
Psrn Kilang Pengkalan 26
3,014 sqft · RM86 PSF
RM285,000
Persiaran Perindustrian Pengkalan 22
3,014 sqft · RM95 PSF
RM265,000
Psrn Kilang Pengkalan 22
2,992 sqft · RM89 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

Commercial

RM285,000

RM95 psf

Median transaction price

Pengkalan Maju Industrial Park in Kinta, Perak recorded 7 Terraced Factory properties subsale transactions between 2021 and 2026, with a median price of RM285K and a median price per square foot (PSF) of RM95.

This area consists exclusively of commercial properties, with no residential listings recorded.

Price remained flat, and PSF growth was PSF remained flat. The median price is RM285K, with most transactions falling within a stable range of RM260K to RM310K, and a typical market range of RM260K to RM325K.

Within the Terraced Factory category, semi-detached factory/warehouse dominated the market, with high diversity across multiple property types.

For price per square foot, the median is RM95, with most transactions between RM86 and RM103. The usual range is RM84.44 to RM104.69, showing that most units are priced quite close to each other. A typical spread (IQR) of RM20.25 and an average deviation (MAD) of RM8 indicate a highly stable PSF trend across properties.

While the area has shown positive growth trends, price variations suggest a more dynamic market. This presents opportunities for investors comfortable with moderate volatility. Significant price variations suggest comparing multiple properties and timing the market carefully. Limited transaction history suggests carefully evaluating comparable sales data.