Bandar Uni. Teknologi Lagenda (Sri Sena)

Taman Permai Jaya, 71700 Mantin, Negeri Sembilan, Malaysia

Property Transactions

2 subsales grouped by size

Median
RM57,500
PSF
RM62
Price Size
Period
transactions middle 50% (P25–P75)
950 sqft
Serviced Apt
RM60,000
Level 5
930 sqft · RM65 PSF
RM55,000
Level 3
930 sqft · RM59 PSF
Legend Recent Highest Price Highest PSF

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Selling in Bandar Uni. Teknologi Lagenda (Sri Sena)

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RM57,500
Median sold price
RM61 psf on average

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Selling in Bandar Uni. Teknologi Lagenda (Sri Sena)?

RM57,500 median

That is what Bandar Uni. Teknologi Lagenda (Sri Sena) homes sold for. List yours free and reach the buyers reading this page.

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Bandar Uni. Teknologi Lagenda (Sri Sena)
© OpenStreetMap · CARTO

Taman Permai Jaya, 71700 Mantin, Negeri Sembilan, Malaysia

Maps

Bandar Uni. Teknologi Lagenda (Sri Sena) in Seremban, Negeri Sembilan recorded 2 Serviced Apt properties subsale transactions between 2021 and 2026, with a median price of RM58K and a median price per square foot (PSF) of RM62.

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 RM58K, with most transactions falling within a stable range of RM55K to RM60K, and a typical market range of RM56K to RM60K.

Within the Serviced Apt category, condominium/apartment dominated the market, with moderate diversity in property types available.

For price per square foot, the median is RM62, with most transactions between RM59 and RM65. The usual range is RM59.71 to RM63.96, showing that most units are priced quite close to each other. A typical spread (IQR) of RM4.25 and an average deviation (MAD) of RM3 indicate a highly stable PSF trend across properties.

Overall, the market in this area appears stable with consistent appreciation, making it an attractive option for both investors and homebuyers. Despite diverse property types, prices remain relatively stable, offering options for different buyer preferences. Limited transaction history suggests carefully evaluating comparable sales data.

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