Taman Pengkalan Makmur

Perak, Larut Matang, Pengkalan Aor

Property Transactions

10 subsales grouped by size

Median
RM210,000
PSF
RM169
Period
transactions middle 50% (P25–P75)
1,200 sqft
Terrace
RM230,000
Lorong 1
1,195 sqft · RM193 PSF
RM200,000
Lorong 1
1,195 sqft · RM167 PSF
1,300 sqft
Terrace
RM240,000
Lorong 1
1,302 sqft · RM184 PSF
RM223,000
Lorong 1
1,302 sqft · RM171 PSF
RM200,000
Lorong 3
1,302 sqft · RM154 PSF
RM230,000
Lorong 1
1,302 sqft · RM177 PSF
RM220,000
Lorong 2
1,302 sqft · RM169 PSF
RM196,000
Lorong 2
1,302 sqft · RM150 PSF
RM200,000
Lorong 1
1,302 sqft · RM154 PSF
RM160,000
Lorong 3
1,302 sqft · RM123 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

Residential

RM210,000

RM168 psf

Median transaction price

Taman Pengkalan Makmur
© OpenStreetMap · CARTO

Taman Pengkalan Makmur, Larut Matang, Perak

Taman Pengkalan Makmur in Larut Matang, Perak recorded 10 subsale transactions between 2021 and 2026, with a median price of RM210K and a median price per square foot (PSF) of RM169.

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

Price remained flat, and PSF growth was PSF remained flat. The median price is RM210K, with most transactions falling within a stable range of RM197K to RM224K, and a typical market range of RM196K to RM224K.

Most transactions involved 1 - 1 1/2 storey terraced, with minimal variety in property types.

For price per square foot, the median is RM169, with most transactions between RM155 and RM183. The usual range is RM158.17 to RM179.67, showing that most units are priced quite close to each other. A typical spread (IQR) of RM21.50 and an average deviation (MAD) of RM14 indicate a highly stable PSF trend across properties.

Overall, the market in this area appears stable with consistent appreciation, making it an attractive option for both investors and homebuyers. The consistent property type and stable pricing make it easier to assess value and compare trends. Limited transaction history suggests carefully evaluating comparable sales data.