Taman Kuang Indah

14000 Bukit Mertajam, Pulau Pinang, Malaysia

Property Transactions

4 subsales grouped by size

Median
RM 480,000
PSF
RM 256
Price Size
Period
transactions middle 50% (P25–P75)
1,850 sqft
2-Sty Terrace
RM 480,000
Lorong Kuang Indah 2
1,873 sqft · RM 256 PSF
RM 480,000
Lorong Kuang Indah 1
1,873 sqft · RM 256 PSF
RM 480,000
Lorong Kuang Indah 1
1,873 sqft · RM 256 PSF
RM 455,000
Lorong Kuang Indah 2
1,873 sqft · RM 243 PSF
Legend Recent Highest Price Highest PSF

Posts about Taman Kuang Indah

What’s happening in Taman Kuang Indah?

No posts about Taman Kuang Indah yet. Be the first to share what’s happening here.

Property News

More property news →

Market Snapshot

Residential

RM 480,000

RM 256 psf

Median transaction price

Loading map...

Taman Kuang Indah, 14000 Bukit Mertajam, Pulau Pinang, Malaysia

Maps

Taman Kuang Indah in Seberang Perai Selatan, Penang recorded 4 subsale transactions in 2022, with a median price of RM 480K and a median price per square foot (PSF) of RM 256.

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 480K, with most transactions falling within a stable range of RM 469K to RM 480K, and a typical market range of RM 478K to RM 480K.

Most transactions involved 2 - 2 1/2 storey terraced, with minimal variety in property types.

For price per square foot, the median is RM 256, with most transactions between RM 250 and RM 262. The usual range is RM 253.28 to RM 259.28, showing that most units are priced quite close to each other. A typical spread (IQR) of RM 6.00 and an average deviation (MAD) of RM 6 indicate a highly stable PSF trend across properties.

Overall, the market in this area appears stable with consistent appreciation, making it an attractive option for both investors and homebuyers. The consistent property type and stable pricing make it easier to assess value and compare trends. Limited transaction history suggests carefully evaluating comparable sales data.