Taman Murni

Sikamat, Pantai, Negeri Sembilan, Malaysia

Property Transactions

8 subsales grouped by size · LC House →

Median
RM 225,000
PSF
RM 209
Price Size
Period
transactions middle 50% (P25–P75)
1,100 sqft
LC House
RM 170,000
Persiaran Desa Rhu 1
1,076 sqft · RM 158 PSF
RM 200,000
Jalan Desa Rhu 19
1,076 sqft · RM 186 PSF
RM 250,000
Jalan Desa Rhu 24
1,076 sqft · RM 232 PSF
RM 250,000
Off Jalan Desa Rhu 14
1,076 sqft · RM 232 PSF
RM 250,000
Jalan Desa Rhu 13
1,076 sqft · RM 232 PSF
RM 170,000
Jalan Desa Rhu 22
1,076 sqft · RM 158 PSF
1,150 sqft
Terrace
RM 290,000
Jalan Desa Rhu 15
1,173 sqft · RM 247 PSF
RM 190,000
Jalan Desa Rhu 15
1,173 sqft · RM 162 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

Residential

RM 225,000

RM 209 psf

Median transaction price

Taman Murni
© OpenStreetMap · CARTO

Sikamat, Pantai, Negeri Sembilan, Malaysia

Maps

Taman Murni in Seremban, Negeri Sembilan recorded 8 subsale transactions between 2021 and 2026, with a median price of RM 225K and a median price per square foot (PSF) of RM 209.

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 RM 225K, with most transactions falling within a stable range of RM 183K to RM 267K, and a typical market range of RM 193K to RM 258K.

Most transactions involved low-cost house, though some variety exists in the market.

The median PSF stands at RM 209, with core pricing between RM 173 and RM 245. Market pricing typically extends from RM 173.53 to RM 244.53, reflecting moderate variation in unit pricing. The spread of RM 71.00 (IQR) and deviation of RM 36 (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.