Ken Rimba Sek. 16
Ken Rimba, Rimba Jaya, 41300 Shah Alam, Selangor, Malaysia
Ken Rimba, Rimba Jaya, 41300 Shah Alam, Selangor, Malaysia
| Road | Price | PSF | Size | Date | Type |
|---|
|
Jalan Lengkuas 16/22
|
RM720,000
|
RM461
|
1,561 sqft
|
|
|
|
Jalan Lengkuas 16/23A
|
RM1,071,000
|
RM686
|
1,561 sqft
|
|
|
|
Jalan Lengkuas 16/25C
|
RM780,000
|
RM500
|
1,561 sqft
|
|
|
|
Jalan Lengkuas 16/21
|
RM640,000
|
RM410
|
1,561 sqft
|
|
|
|
Jalan Lengkuas 16/22A
|
RM660,000
|
RM423
|
1,561 sqft
|
|
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Ken Rimba Sek. 16
Pangsapuri Rimba 2
PSF median price per sq ft · 12m its change over the past 12 months
Most-traded areas in this mukim, by number of recorded subsale transactions. See every area in Kapar
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Market Snapshot
ResidentialRM720,000
RM461 psfMedian transaction price
Ken Rimba, Rimba Jaya, 41300 Shah Alam, Selangor, Malaysia
MapsKen Rimba Sek. 16 in Klang, Selangor recorded 5 subsale transactions between 2021 and 2026, with a median price of RM720K and a median price per square foot (PSF) of RM461.
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 RM720K, with most transactions falling within a stable range of RM640K to RM876K, and a typical market range of RM640K to RM916K.
Most transactions involved 2 - 2 1/2 storey terraced, with minimal variety in property types.
Price per square foot shows a median of RM461, though individual units vary from RM361 to RM561 in the core range. The broader market spans RM416.00 to RM506.00, indicating diverse property characteristics. The spread of RM90.00 (IQR) and deviation of RM100 (MAD) suggest moderate price variations reflecting different property features.
While the area has shown positive growth trends, price variations suggest a more dynamic market. This presents opportunities for investors comfortable with moderate volatility. Some price volatility exists, making thorough market research essential before transacting. Limited transaction history suggests carefully evaluating comparable sales data.