Taman Maju

43000 Kajang, Selangor, Malaysia

Property Transactions

13 subsales found

Period
transactions middle 50% (P25–P75)
RM 420,000
Jalan 8
900 sqft RM 467 PSF
RM 500,000
Jalan 2
1,216 sqft RM 411 PSF
RM 430,000
Jalan 7
1,300 sqft RM 331 PSF
RM 415,000
Jalan 9
825 sqft RM 503 PSF
RM 460,000
Jalan 2
1,216 sqft RM 378 PSF
RM 410,000
Jalan 7
1,119 sqft RM 366 PSF
RM 550,000
Jalan Maju 7
3,988 sqft RM 138 PSF
RM 435,000
Jalan 2
1,216 sqft RM 358 PSF
RM 200,000
Jalan 9
825 sqft RM 242 PSF
RM 450,000
Jalan. 2
1,216 sqft RM 370 PSF
RM 260,000
Jalan 8
900 sqft RM 289 PSF
RM 245,000
Jalan 4
825 sqft RM 297 PSF
RM 450,000
Jalan 7
1,119 sqft RM 402 PSF
13
transactions

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Market Snapshot

Residential

RM 430,000

RM 297 psf

Median transaction price

Taman Maju
© OpenStreetMap · CARTO

Taman Maju, 43000 Kajang, Selangor, Malaysia

Maps

Taman Maju in Hulu Langat, Selangor recorded 13 subsale transactions between 2021 and 2026, with a median price of RM 430K and a median price per square foot (PSF) of RM 366.

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 RM 430K, with most transactions falling within a stable range of RM 410K to RM 450K, and a typical market range of RM 410K to RM 450K.

Most transactions involved 2 - 2 1/2 storey terraced, with moderate diversity in property types available.

For price per square foot, the median is RM 366, with most transactions between RM 333 and RM 399. The usual range is RM 337.25 to RM 395.25, showing that most units are priced quite close to each other. With an IQR of RM 58.00 and MAD of RM 33, the PSF demonstrates reasonable consistency across the market.

Overall, the market in this area appears stable with consistent appreciation, making it an attractive option for both investors and homebuyers. Despite diverse property types, prices remain relatively stable, offering options for different buyer preferences. Limited transaction history suggests carefully evaluating comparable sales data.