Larkin Perdana

Taman Larkin Perdana, 80350 Johor Bahru, Johor Darul Ta'zim, Malaysia

Property Transactions

5 subsales grouped by size · Condo →

Median
RM 185,000
PSF
RM 286
Price Size
Period
transactions middle 50% (P25–P75)
650 sqft
LC Flat
RM 185,000
Level 3
646 sqft · RM 286 PSF
RM 170,000
Level 4
646 sqft · RM 263 PSF
RM 150,000
Level 4
646 sqft · RM 232 PSF
900 sqft
Condo
RM 255,000
Level 20
883 sqft · RM 289 PSF
950 sqft
Condo
RM 350,000
Level 11
947 sqft · RM 370 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

RM 185,000

RM 286 psf

Median transaction price

RM 168,000

RM 114 psf

Median transaction price

Larkin Perdana
© OpenStreetMap · CARTO

Taman Larkin Perdana, 80350 Johor Bahru, Johor Darul Ta'zim, Malaysia

Maps

Larkin Perdana in Johor Bahru, Johor recorded 5 subsale transactions between 2021 and 2026, with a median price of RM 185K and a median price per square foot (PSF) of RM 286.

This area contains both residential and commercial properties. View 155 residential properties or 25 commercial properties separately for more focused analysis.

Price remained flat, and PSF growth was PSF remained flat. The median price is RM 185K, with most transactions falling within a stable range of RM 150K to RM 258K, and a typical market range of RM 153K to RM 217K.

Most transactions involved condominium/apartment, with moderate diversity in property types available.

The median PSF stands at RM 286, with core pricing between RM 240 and RM 332. Market pricing typically extends from RM 257.38 to RM 314.63, reflecting moderate variation in unit pricing. The spread of RM 57.25 (IQR) and deviation of RM 46 (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.