Taman Perindustrian. Perdana Lukut

Taman Perindustrian Perdana Bukit Palong, Lukut, Negeri Sembilan, Malaysia

Property Transactions

8 subsales grouped by size

Median
RM290,000
PSF
RM155
Period
transactions middle 50% (P25–P75)
1,950 sqft
Terrace Factory
RM370,000
Jalan Perdana 6
1,938 sqft · RM191 PSF
RM600,000
Jalan Perdana 3
1,938 sqft · RM310 PSF
RM375,000
Jalan Perdana 5
1,938 sqft · RM194 PSF
RM260,000
Jalan Perdana 5
1,938 sqft · RM134 PSF
RM300,000
Jalan Perdana 5
1,938 sqft · RM155 PSF
RM220,000
Jalan Perdana 4
1,938 sqft · RM114 PSF
RM277,000
Jalan Perdana 4
1,938 sqft · RM143 PSF
2,350 sqft
Terrace Factory
RM280,000
Jalan Perdana 2
2,325 sqft · RM120 PSF
Legend Recent Highest Price Highest PSF

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Taman Perindustrian. Perdana Lukut
© OpenStreetMap · CARTO

Taman Perindustrian Perdana Bukit Palong, Lukut, Negeri Sembilan, Malaysia

Maps

Taman Perindustrian. Perdana Lukut in Port Dickson, Negeri Sembilan recorded 8 subsale transactions between 2021 and 2026, with a median price of RM290K and a median price per square foot (PSF) of RM155.

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 RM290K, with most transactions falling within a stable range of RM240K to RM340K, and a typical market range of RM241K to RM339K.

Most transactions involved terraced factory/warehouse, with minimal variety in property types.

The median PSF stands at RM155, with core pricing between RM138 and RM171. Market pricing typically extends from RM141.97 to RM167.72, reflecting moderate variation in unit pricing. With an IQR of RM25.75 and MAD of RM17, the PSF demonstrates reasonable consistency across the market.

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.