| LIST.MY · Persiaran Cinta Sayang | |||||
|---|---|---|---|---|---|
|
Road
|
Price
|
PSF
|
Size
|
Date
|
Type
|
| 2026 | |||||
|
Jalan Persiaran Cinta Sayang
|
RM490,000
|
RM82
|
6,000 sqft
|
|
Bungalow |
| 2022 | |||||
|
Persiaran Cinta Sayang
|
RM600,000
|
RM100
|
6,000 sqft
|
|
Bungalow |
| 2021 | |||||
|
Persiaran Cinta Sayang
|
RM600,000
|
RM100
|
6,000 sqft
|
|
Bungalow |
Selling in Persiaran Cinta Sayang? Homes here sold for a median of RM600,000.
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Persiaran Cinta Sayang
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 Sungai Petani
Market Snapshot
ResidentialRM600,000
RM100 psfMedian transaction price
PERSIARAN CINTA SAYANG, Bandar Sungai Petani, 08000, Kuala Muda, Kedah, Malaysia
Persiaran Cinta Sayang in Kuala Muda, Kedah recorded 3 subsale transactions between 2021 and 2026, sized between 5,975 and 6,024 sqft, with a median price of RM600K and a median price per square foot (PSF) of RM100.
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 RM600K, with most transactions falling within a stable range of RM548K to RM600K, and a typical market range of RM490K to RM600K.
Most transactions involved detached, with minimal variety in property types.
For price per square foot, the median is RM100, with most transactions between RM92 and RM108. The usual range is RM84.00 to RM116.00, showing that most units are priced quite close to each other. A typical spread (IQR) of RM32.00 and an average deviation (MAD) of RM8 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. Some price volatility exists, making thorough market research essential before transacting. Limited transaction history suggests carefully evaluating comparable sales data.