Taman Makmur

70200 Seremban, Negeri Sembilan, Malaysia

Property Transactions

8 subsales found

Price Size
Period
transactions middle 50% (P25–P75)
RM356,000
Jalan Bijih Timah 11
1,765 sqft RM202 PSF
RM313,000
Jalan Bijih Timah 4
1,765 sqft RM177 PSF
RM326,000
Jalan Bijih Timah 8
1,765 sqft RM185 PSF
RM340,000
Lorong Bijih Timah 10/1
1,765 sqft RM193 PSF
RM350,000
Off Jalan Tun Dr Ismail
1,765 sqft RM198 PSF
RM300,000
Jalan Bijih Timah 1
1,765 sqft RM170 PSF
RM346,000
Jalan Bijih Timah 9
1,765 sqft RM196 PSF
RM268,000
Lorong Bijih Timah 10/3
1,765 sqft RM152 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

Residential

RM333,000

RM189 psf

Median transaction price

Taman Makmur
© OpenStreetMap · CARTO

Taman Makmur, 70200 Seremban, Negeri Sembilan, Malaysia

Maps

Taman Makmur in Seremban, Negeri Sembilan recorded 8 subsale transactions between 2021 and 2026, sized between 1,725 and 1,774 sqft, with a median price of RM333K and a median price per square foot (PSF) of RM189.

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 RM333K, with most transactions falling within a stable range of RM305K to RM356K, and a typical market range of RM268K to RM356K.

Most transactions involved 1 - 1 1/2 storey terraced, with moderate diversity in property types available.

For price per square foot, the median is RM189, with most transactions between RM173 and RM205. The usual range is RM160.02 to RM217.27, showing that most units are priced quite close to each other. With an IQR of RM57.25 and MAD of RM16, the PSF demonstrates reasonable consistency across the market.

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.