| Road | Price | PSF | Size | Date | Type |
|---|
|
Psrn Kilang Pengkalan 26
|
RM 600,000
|
RM 120
|
5,005 sqft
|
|
|
|
Psrn Kilang Pengkalan 28
|
RM 600,000
|
RM 120
|
5,005 sqft
|
|
|
|
Psrn Perindustrian Pgkln 24
|
RM 715,000
|
RM 143
|
5,005 sqft
|
|
|
|
Psrn Kilang Pengkalan 28
|
RM 650,000
|
RM 130
|
5,005 sqft
|
|
|
Psrn Perindustrian Pgkln 24
|
RM 715,000
|
RM 137
|
5,210 sqft
|
|
|
Persiaran Kilang Pengkalan 22
|
RM 690,000
|
RM 125
|
5,500 sqft
|
|
|
|
Psrn Kilang Pengkalan 22
|
RM 596,000
|
RM 108
|
5,500 sqft
|
|
|
Persiaran Perindustrian Pengkalan 28
|
RM 750,000
|
RM 112
|
6,684 sqft
|
|
|
Psrn Kilang Pengkalan 28
|
RM 1,300,000
|
RM 130
|
10,000 sqft
|
|
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Market Snapshot
CommercialRM 690,000
RM 125 psfMedian transaction price
Pengkalan Maju Industrial Park in Kinta, Perak recorded 9 Semi-D Factory properties subsale transactions between 2021 and 2026, with a median price of RM 690K and a median price per square foot (PSF) of RM 125.
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 RM 690K, with most transactions falling within a stable range of RM 596K to RM 897K, and a typical market range of RM 596K to RM 953K.
Within the Semi-D Factory category, semi-detached factory/warehouse dominated the market, with high diversity across multiple property types.
For price per square foot, the median is RM 125, with most transactions between RM 115 and RM 136. The usual range is RM 115.33 to RM 135.58, showing that most units are priced quite close to each other. A typical spread (IQR) of RM 20.25 and an average deviation (MAD) of RM 11 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.