Taman Setapak Indah

Lorong Penghulu, Gombak Setia, 53100 Kuala Lumpur, Selangor, Malaysia

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From
RM600K
Size
800 sqft

Property Transactions

6 subsales grouped by size

Price Size
Period
transactions middle 50% (P25–P75)
650 sqft
LC Flat
RM210,000
Level 1
646 sqft · RM325 PSF
RM240,000
Level 3
646 sqft · RM372 PSF
RM245,000
Level G
646 sqft · RM379 PSF
RM260,000
Level 1
646 sqft · RM403 PSF
RM200,000
Level 2
646 sqft · RM310 PSF
1,250 sqft
2-Sty Terrace
RM645,000
Jalan 2C/6
1,259 sqft · RM512 PSF
Legend Recent Highest Price Highest PSF

Selling in Taman Setapak Indah? Homes here sold for a median of RM242,500.

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Market Snapshot

Residential

RM242,500

RM375 psf

Median transaction price

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Lorong Penghulu, Gombak Setia, 53100 Kuala Lumpur, Selangor, Malaysia

Maps

Taman Setapak Indah in Kuala Lumpur, Kuala Lumpur recorded 6 subsale transactions between 2021 and 2026, with a median price of RM243K and a median price per square foot (PSF) of RM375.

This area contains both residential and commercial properties. View 39 residential properties or 3 commercial properties separately for more focused analysis.

Price remained flat, and PSF growth was PSF remained flat. The median price is RM243K, with most transactions falling within a stable range of RM200K to RM398K, and a typical market range of RM200K to RM431K.

Most transactions involved low-cost flat, with moderate diversity in property types available.

The median PSF stands at RM375, with core pricing between RM310 and RM441. Market pricing typically extends from RM337.62 to RM413.37, reflecting moderate variation in unit pricing. The spread of RM75.75 (IQR) and deviation of RM66 (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.