Pulau Indah Industrial Park

42000 Pulau Indah, Selangor, Malaysia

Property Transactions

5 subsales grouped by size

Median
RM2,000,000
PSF
RM231
Price Size
Period
transactions middle 50% (P25–P75)
3,050 sqft
Terrace Factory
RM700,000
Jalan Perigi Nenas 8/10
3,035 sqft · RM231 PSF
RM700,000
Jalan Perigi Nenas 8/10
3,035 sqft · RM231 PSF
7,200 sqft
Semi-D Factory
RM2,000,000
Jalan Perigi Nanas 8/12
7,200 sqft · RM278 PSF
174,200 sqft
Factory
RM23,000,000
Jalan Perigi Nenas 7/2
174,225 sqft · RM132 PSF
196,550 sqft
Factory
RM48,569,000
Jalan Perigi Nanas 7/2/Ks11
196,562 sqft · RM247 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

Commercial

RM2,000,000

RM231 psf

Median transaction price

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Pulau Indah Industrial Park, 42000 Pulau Indah, Selangor, Malaysia

Maps

Pulau Indah Industrial Park in Klang, Selangor recorded 5 subsale transactions in 2024, with a median price of RM2.00 million and a median price per square foot (PSF) of RM231.

This area consists exclusively of commercial properties, with no residential listings recorded.

Price remained flat, and PSF growth was PSF remained flat. The median price is RM2.00 million, with most transactions falling within a stable range of RM700K to RM20.81 million, and a typical market range of RM700K to RM6.02 million.

Most transactions involved terraced factory/warehouse, with high diversity across multiple property types.

Price per square foot shows a median of RM231, though individual units vary from RM182 to RM280 in the core range. The broader market spans RM179.61 to RM281.61, indicating diverse property characteristics. The spread of RM102.00 (IQR) and deviation of RM49 (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. Significant price variations suggest comparing multiple properties and timing the market carefully. Limited transaction history suggests carefully evaluating comparable sales data.