Ken Rimba Sek. 16

Ken Rimba, Rimba Jaya, 41300 Shah Alam, Selangor, Malaysia

Property Transactions

9 subsales grouped by size

Median
RM 750,000
PSF
RM 481
Price Size
Period
transactions middle 50% (P25–P75)
1,550 sqft
2-Sty Terrace
RM 1,054,000
Jalan Lengkuas 16/25E
1,561 sqft · RM 675 PSF
RM 1,054,000
Jalan Lengkuas 16/25F
1,561 sqft · RM 675 PSF
RM 1,046,000
Jalan Lengkuas 16/25H
1,561 sqft · RM 670 PSF
RM 588,000
Jalan Lengkuas 16/22
1,561 sqft · RM 377 PSF
RM 1,116,000
Jalan Lengkuas 16/22A
1,561 sqft · RM 715 PSF
RM 645,000
Jalan Lengkuas 16/21
1,561 sqft · RM 413 PSF
+3 more
Legend Recent Highest Price Highest PSF

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Market Snapshot

Residential

RM 750,000

RM 481 psf

Median transaction price

Ken Rimba Sek. 16
© OpenStreetMap · CARTO

Ken Rimba, Rimba Jaya, 41300 Shah Alam, Selangor, Malaysia

Maps

Ken Rimba Sek. 16 in Klang, Selangor recorded 9 subsale transactions in 2021, with a median price of RM 750K and a median price per square foot (PSF) of RM 481.

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 RM 750K, with most transactions falling within a stable range of RM 588K to RM 960K, and a typical market range of RM 588K to RM 946K.

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

Price per square foot shows a median of RM 481, though individual units vary from RM 346 to RM 615 in the core range. The broader market spans RM 435.53 to RM 525.53, indicating diverse property characteristics. A wider spread (IQR: RM 90.00) and deviation (MAD: RM 135) 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. Some price volatility exists, making thorough market research essential before transacting. Limited transaction history suggests carefully evaluating comparable sales data.