Sri Sena @Bandar Uni. Teknologi Lagenda

Taman Permai Jaya, 71700 Mantin, Negeri Sembilan, Malaysia

Property Transactions

5 subsales grouped by size

Median
RM58,000
PSF
RM70
Period
transactions middle 50% (P25–P75)
650 sqft
Serviced Apt
RM40,000
Level 1
665 sqft · RM60 PSF
RM58,000
Level 1
665 sqft · RM87 PSF
950 sqft
Serviced Apt
RM100,000
Level 1
930 sqft · RM108 PSF
RM65,000
Level 2
930 sqft · RM70 PSF
RM52,000
Level 3
930 sqft · RM56 PSF
Legend Recent Highest Price Highest PSF

Posts about Sri Sena @Bandar Uni. Teknologi Lagenda

What’s happening in Sri Sena @Bandar Uni. Teknologi Lagenda?

No posts about Sri Sena @Bandar Uni. Teknologi Lagenda yet. Be the first to share what’s happening here.

Sri Sena @Bandar Uni. Teknologi Lagenda
© OpenStreetMap · CARTO

Taman Permai Jaya, 71700 Mantin, Negeri Sembilan, Malaysia

Maps

Sri Sena @Bandar Uni. Teknologi Lagenda in Seremban, Negeri Sembilan recorded 5 subsale transactions between 2021 and 2026, with a median price of RM58K and a median price per square foot (PSF) of RM70.

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 RM51K to RM65K, and a typical market range of RM52K to RM65K.

Most transactions involved serviced apartment, with minimal variety in property types.

Price per square foot shows a median of RM70, though individual units vary from RM56 to RM84 in the core range. The broader market spans RM56.39 to RM83.39, indicating diverse property characteristics. The spread of RM27.00 (IQR) and deviation of RM14 (MAD) suggest moderate price variations reflecting different property features.

Overall, the market in this area appears stable with consistent appreciation, making it an attractive option for both investors and homebuyers. Moderate price stability provides a balanced market for both buyers and sellers. Limited transaction history suggests carefully evaluating comparable sales data.