Taman Setia Kasih [Sikamat]

1, Jalan setia Kasih 2, taman setia kasih, 72000 Kuala pilah, Negeri Sembilan, Malaysia

Property Transactions

4 subsales grouped by size

Price Size
Period
transactions middle 50% (P25–P75)
1,200 sqft
LC House
RM350,000
Lorong Desarhu 11/4
1,195 sqft · RM293 PSF
RM110,000
Lorong Desarhu 11/4
1,195 sqft · RM92 PSF
3,350 sqft
LC House
RM180,000
Jalan Desa Rhu 3
3,326 sqft · RM54 PSF
RM180,000
Jalan Desa Rhu 3
3,326 sqft · RM54 PSF
Legend Recent Highest Price Highest PSF

Selling in Taman Setia Kasih [Sikamat]? Homes here sold for a median of RM180,000.

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Taman Setia Kasih [Sikamat]
© OpenStreetMap · CARTO

1, Jalan setia Kasih 2, taman setia kasih, 72000 Kuala pilah, Negeri Sembilan, Malaysia

Maps

Taman Setia Kasih [Sikamat] in Seremban, Negeri Sembilan recorded 4 Low-Cost House properties subsale transactions between 2021 and 2026, with a median price of RM180K and a median price per square foot (PSF) of RM73.

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 RM180K, with most transactions falling within a stable range of RM110K to RM268K, and a typical market range of RM130K to RM230K.

Within the Low-Cost House category, low-cost house dominated the market, though some variety exists in the market.

Price per square foot shows a median of RM73, though individual units vary from RM0 to RM172 in the core range. The broader market spans RM0.00 to RM163.09, indicating diverse property characteristics. A wider spread (IQR: RM180.00) and deviation (MAD: RM99) 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.