Taman Medan Lapangan Sentosa

Perak, Kinta, Ulu Kinta

Property Transactions

17 subsales grouped by road

Period
transactions middle 50% (P25–P75)
RM220,000
1,302 sqft
RM169 PSF · Terrace
RM240,000
1,302 sqft
RM184 PSF · LC House
RM185,000
1,302 sqft
RM142 PSF · LC House
RM200,000
2,486 sqft
RM80 PSF · LC House
RM180,000
1,302 sqft
RM138 PSF · LC House
RM180,000
1,948 sqft
RM92 PSF
RM144,000
1,302 sqft
RM111 PSF
RM270,000
2,486 sqft
RM109 PSF
RM200,000
1,302 sqft
RM154 PSF · LC House
RM200,000
1,302 sqft
RM154 PSF · LC House
RM170,000
1,302 sqft
RM131 PSF · Terrace
RM210,000
1,302 sqft
RM161 PSF
RM199,000
1,302 sqft
RM153 PSF
RM210,000
1,302 sqft
RM161 PSF
RM220,000
1,948 sqft
RM113 PSF
RM195,000
1,302 sqft
RM150 PSF
RM208,000
1,302 sqft
RM160 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

Residential

RM200,000

RM150 psf

Median transaction price

Taman Medan Lapangan Sentosa in Kinta, Perak recorded 17 subsale transactions between 2021 and 2026, with a median price of RM200K and a median price per square foot (PSF) of RM150.

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 RM200K, with most transactions falling within a stable range of RM185K to RM215K, and a typical market range of RM188K to RM213K.

Most transactions involved low-cost house, though some variety exists in the market.

For price per square foot, the median is RM150, with most transactions between RM138 and RM162. The usual range is RM126.22 to RM173.22, showing that most units are priced quite close to each other. A typical spread (IQR) of RM47.00 and an average deviation (MAD) of RM12 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.