Park Cherang Guling
Alur Limbat, Bukit Payong, Terengganu, Malaysia
Alur Limbat, Bukit Payong, Terengganu, Malaysia
| Road | Price | PSF | Size | Date | Type |
|---|
|
Cherang Cina, Off Jalan Durian Guling
|
RM190,000
|
RM159
|
1,195 sqft
|
|
Selling in Park Cherang Guling? Homes here sold for a median of RM190,000.
Free to list, about two minutes, and the buyers reading this page will see it.
Posts about Park Cherang Guling
No posts about Park Cherang Guling yet. Be the first to share what’s happening here.
Nearby areas in Alur Limbat
Taman Rawai Perdana
Rawai
Tasek
Alur Limbat
Binjai Rendah
Park Cherang Guling
Bukit Payong
Durian Guling
Taman Desa Salam (Mr 29-00)
Banggol Katong
Padang Limau Nipis
Telaga Mengkudu
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 Alur Limbat
Market Snapshot
ResidentialRM190,000
RM159 psfMedian transaction price
Alur Limbat, Bukit Payong, Terengganu, Malaysia
MapsPark Cherang Guling in Marang, Terengganu recorded 1 subsale transactions in 2025, with a median price of RM190K and a median price per square foot (PSF) of RM159.
This area consists exclusively of residential properties, with no commercial listings recorded.
Price remained flat, and PSF growth was PSF remained flat.
Most transactions involved low-cost house, with moderate diversity in property types available.
For price per square foot, the median is RM159, with most transactions between RM159 and RM159. The usual range is RM118.52 to RM199.52, showing that most units are priced quite close to each other. With an IQR of RM81.00 and MAD of RM0, the PSF demonstrates reasonable consistency across the market.
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.