Taman Nesa@Manicharasegam

Taman Nesa, 81300 Skudai, Johor Darul Ta'zim, Malaysia

Property Transactions

6 subsales grouped by size

Price Size
Period
transactions middle 50% (P25–P75)
1,050 sqft
LC House
RM245,000
Jalan Joget 1
1,044 sqft · RM235 PSF
RM170,000
Jalan Joget 4
1,044 sqft · RM163 PSF
1,550 sqft
Terrace
RM410,000
Jalan Joget 6
1,540 sqft · RM266 PSF
RM410,000
Jalan Ronggeng 19
1,539 sqft · RM266 PSF
RM380,000
Jalan Joget 6
1,539 sqft · RM247 PSF
RM305,000
Jalan Ronggeng 29
1,540 sqft · RM198 PSF
Legend Recent Highest Price Highest PSF

Selling in Taman Nesa@Manicharasegam? Homes here sold for a median of RM342,500.

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Market Snapshot

Residential

RM342,500

RM241 psf

Median transaction price

Taman Nesa@Manicharasegam
© OpenStreetMap · CARTO

Taman Nesa, 81300 Skudai, Johor Darul Ta'zim, Malaysia

Maps

Taman Nesa@Manicharasegam in Johor Bahru, Johor recorded 6 subsale transactions in 2021, with a median price of RM343K and a median price per square foot (PSF) of RM241.

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 RM343K, with most transactions falling within a stable range of RM253K to RM410K, and a typical market range of RM276K to RM409K.

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

The median PSF stands at RM241, with core pricing between RM203 and RM278. Market pricing typically extends from RM215.14 to RM266.39, reflecting moderate variation in unit pricing. The spread of RM51.25 (IQR) and deviation of RM38 (MAD) suggest moderate price variations reflecting different property features.

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.