Kampung Baru Rimba Panjang

Sungei Siput, 30100, Kuala Kangsar, Perak, Malaysia

Property Transactions

5 subsales grouped by size

Price Size
Period
transactions middle 50% (P25–P75)
3,700 sqft
Bungalow
RM500,000
Kampung. Baru Rimba Panjang
3,681 sqft · RM136 PSF
3,800 sqft
Bungalow
RM86,000
Jalan Chemor-Sungai Siput
3,790 sqft · RM23 PSF
3,850 sqft
Bungalow
RM270,000
Kampung. Baru Rimba Panjang
3,853 sqft · RM70 PSF
3,900 sqft
Bungalow
RM200,000
Sungai Siput
3,897 sqft · RM51 PSF
3,950 sqft
Bungalow
RM327,000
Kampung Baru Rimba Panjang
3,940 sqft · RM83 PSF
Legend Recent Highest Price Highest PSF

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KAMPUNG BARU RIMBA PANJANG, Sungei Siput, 30100, Kuala Kangsar, Perak, Malaysia

Kampung Baru Rimba Panjang in Kuala Kangsar, Perak recorded 5 Bungalow properties subsale transactions between 2021 and 2026, with a median price of RM270K and a median price per square foot (PSF) of RM70.

This area contains both residential and commercial properties. View 5 residential properties or 1 commercial properties separately for more focused analysis.

Price remained flat, and PSF growth was PSF remained flat. The median price is RM270K, with most transactions falling within a stable range of RM132K to RM408K, and a typical market range of RM158K to RM382K.

Within the Bungalow category, detached dominated the market, though some variety exists in the market.

Price per square foot shows a median of RM70, though individual units vary from RM33 to RM108 in the core range. The broader market spans RM44.44 to RM95.70, indicating diverse property characteristics. A wider spread (IQR: RM51.25) and deviation (MAD: RM37) indicate significant PSF variations, likely due to diverse property types or conditions.

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.