Taman Angkasa Indah

43000 Kajang, Selangor, Malaysia

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From
RM600K
Size
800 sqft

Property Transactions

7 subsales grouped by size

Period
transactions middle 50% (P25–P75)
650 sqft
LC Flat
RM140,000
Level 4
667 sqft · RM210 PSF
RM155,000
Level 3
667 sqft · RM232 PSF
RM130,000
Level 5
667 sqft · RM195 PSF
1,500 sqft
2-Sty Terrace
RM715,000
Jalan Angkasa Indah 1E
1,496 sqft · RM478 PSF
1,600 sqft
2-Sty Terrace
RM675,000
Jalan Angkasa Indah 3
1,593 sqft · RM424 PSF
RM750,000
Jalan Angkasa Indah 2A
1,593 sqft · RM471 PSF
4,800 sqft
Bungalow
RM1,050,000
Jalan Angkasa Indah 1
4,801 sqft · RM219 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

Residential

RM675,000

RM221 psf

Median transaction price

Taman Angkasa Indah
© OpenStreetMap · CARTO

Taman Angkasa Indah, 43000 Kajang, Selangor, Malaysia

Maps

Taman Angkasa Indah in Hulu Langat, Selangor recorded 7 subsale transactions between 2021 and 2026, with a median price of RM675K and a median price per square foot (PSF) of RM232.

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 RM675K, with most transactions falling within a stable range of RM300K to RM1.05 million, and a typical market range of RM383K to RM968K.

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

For price per square foot, the median is RM232, with most transactions between RM221 and RM243. The usual range is RM218.51 to RM246.01, showing that most units are priced quite close to each other. A typical spread (IQR) of RM27.50 and an average deviation (MAD) of RM11 indicate a highly stable PSF trend across properties.

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.