| LIST.MY · Taman Gurun Indah | |||||
|---|---|---|---|---|---|
|
Road
|
Price
|
PSF
|
Size
|
Date
|
Type
|
| 2022 | |||||
|
Jalan Gurun Indah 7
|
RM156,000
|
RM95
|
1,647 sqft
|
|
LC House |
|
Jalan Gurun Indah 5
|
RM360,000
|
RM216
|
1,668 sqft
|
|
2-Sty Terrace |
| 2021 | |||||
|
Jalan Gurun Indah 4
|
RM450,000
|
RM270
|
1,668 sqft
|
|
2-Sty Terrace |
|
Jalan Gurun Indah 5
|
RM360,000
|
RM216
|
1,668 sqft
|
|
2-Sty Terrace |
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PSF median price per sq ft · 12m its change over the past 12 months
Most-traded areas in this mukim, by number of recorded subsale transactions. See every area in Bandar Gurun
Market Snapshot
ResidentialRM360,000
RM216 psfMedian transaction price
TAMAN GURUN INDAH, Bandar Gurun, 08300, Kuala Muda, Kedah, Malaysia
Taman Gurun Indah in Kuala Muda, Kedah recorded 4 subsale transactions between 2021 and 2026, sized between 1,625 and 1,674 sqft, with a median price of RM360K and a median price per square foot (PSF) of RM216.
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 RM360K, with most transactions falling within a stable range of RM252K to RM450K, and a typical market range of RM169K to RM450K.
Most transactions involved 2 - 2 1/2 storey semi-detached, with high diversity across multiple property types.
Price per square foot shows a median of RM216, though individual units vary from RM152 to RM280 in the core range. The broader market spans RM162.52 to RM269.02, indicating diverse property characteristics. A wider spread (IQR: RM106.50) and deviation (MAD: RM64) indicate significant PSF variations, likely due to diverse property types or conditions.
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.