| Road | Price | PSF | Size | Date | Type |
|---|
|
Jalan Ds 3/12
|
RM1,005,000
|
RM314
|
3,197 sqft
|
|
|
|
Jalan Ds 3/13
|
RM875,000
|
RM274
|
3,197 sqft
|
|
|
|
Jalan Ds 3/6
|
RM900,000
|
RM282
|
3,197 sqft
|
|
|
|
Jalan Ds 3/13
|
RM880,000
|
RM275
|
3,197 sqft
|
|
|
|
Jalan Ds 3/13
|
RM880,000
|
RM275
|
3,197 sqft
|
|
|
|
Jalan Ds 3/5
|
RM880,000
|
RM275
|
3,197 sqft
|
|
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Segar Avenue
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 Pekan Lukut
Market Snapshot
ResidentialRM880,000
RM275 psfMedian transaction price
Segar Avenue, 1320, Jalan DS 4, Bandar Dataran Segar, 71010 Port Dickson, Negeri Sembilan, Malaysia
MapsSegar Avenue in Port Dickson, Negeri Sembilan recorded 6 Double Storey Semi-D properties subsale transactions between 2021 and 2026, with a median price of RM880K and a median price per square foot (PSF) of RM275.
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 RM880K, with most transactions falling within a stable range of RM875K to RM926K, and a typical market range of RM875K to RM1.01 million.
Within the Double Storey Semi-D category, 2 - 2 1/2 storey semi-detached dominated the market, though some variety exists in the market.
For price per square foot, the median is RM275, with most transactions between RM261 and RM290. The usual range is RM260.65 to RM289.90, showing that most units are priced quite close to each other. A typical spread (IQR) of RM29.25 and an average deviation (MAD) of RM14 indicate a highly stable PSF trend across properties.
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.