Taman Berjaya, Tg Rambutan

Perak, Kinta, Ulu Kinta

Property Transactions

9 subsales grouped by size

Period
transactions middle 50% (P25–P75)
1,100 sqft
LC House
RM150,000
Laluan Sungai Choh 3
1,087 sqft · RM138 PSF
1,200 sqft
Terrace
RM215,000
Laluan Sungai Choh 9A
1,195 sqft · RM180 PSF
RM208,000
Laluan Sungai Choh 9A
1,195 sqft · RM174 PSF
RM200,000
Laluan Sungai Choh 9
1,195 sqft · RM167 PSF
RM220,000
Laluan Sungai Choh 9A
1,195 sqft · RM184 PSF
RM200,000
Laluan Sungai Choh 9A
1,195 sqft · RM167 PSF
1,300 sqft
Terrace
RM230,000
Lalaun Sungai Choh 9
1,324 sqft · RM174 PSF
1,500 sqft
Terrace
RM290,000
Laluan Sungai Choh 9A
1,496 sqft · RM194 PSF
3,650 sqft
LC House
RM330,000
Laluan Sungai Choh 1
3,638 sqft · RM91 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

Residential

RM215,000

RM174 psf

Median transaction price

Taman Berjaya, Tg Rambutan in Kinta, Perak recorded 9 subsale transactions between 2021 and 2026, with a median price of RM215K and a median price per square foot (PSF) of RM174.

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 RM215K, with most transactions falling within a stable range of RM200K to RM230K, and a typical market range of RM200K to RM230K.

Most transactions involved 1 - 1 1/2 storey terraced, though some variety exists in the market.

For price per square foot, the median is RM174, with most transactions between RM167 and RM181. The usual range is RM167.22 to RM180.22, showing that most units are priced quite close to each other. A typical spread (IQR) of RM13.00 and an average deviation (MAD) of RM7 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.