| Road | Price | PSF | Size | Date | Type |
|---|
|
Taman Rawai Perdana, Jalan Kampung Rawai-Pasir Tinggi (Pl
|
RM 255,000
|
RM 212
|
1,206 sqft
|
|
|
|
Taman Rawai Perdana, Jalan Kampung Rawai-Pasir Tinggi (Pl
|
RM 255,000
|
RM 213
|
1,195 sqft
|
|
|
|
Jalan Kampung Rawai-Pasir Tinggi (Pl
|
RM 255,000
|
RM 213
|
1,195 sqft
|
|
|
Jalan Kampung Rawai-Pasir Tinggi (Pl:7211)
|
RM 282,000
|
RM 193
|
1,464 sqft
|
|
|
Jalan Kampung Rawai-Pasir Tinggi (Pl
|
RM 296,000
|
RM 110
|
2,680 sqft
|
|
|
Taman Rawai Perdana, Jalan Kampung Rawai-Pasir Tinggi (Pl
|
RM 356,000
|
RM 128
|
2,788 sqft
|
|
|
|
Jalan Kampung Rawai-Pasir Tinggi (Pl
|
RM 299,000
|
RM 106
|
2,809 sqft
|
|
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Market Snapshot
ResidentialRM 282,000
RM 193 psfMedian transaction price
Taman Rawai Perdana Kampung Padang Limau Nipis, 21400 Marang, Terengganu, Malaysia
MapsTaman Rawai Perdana in Marang, Terengganu recorded 7 subsale transactions between 2021 and 2026, with a median price of RM 282K and a median price per square foot (PSF) of RM 193.
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 282K, with most transactions falling within a stable range of RM 255K to RM 316K, and a typical market range of RM 262K to RM 303K.
Most transactions involved 1 - 1 1/2 storey terraced, though some variety exists in the market.
Price per square foot shows a median of RM 193, though individual units vary from RM 146 to RM 240 in the core range. The broader market spans RM 162.50 to RM 223.50, indicating diverse property characteristics. The spread of RM 61.00 (IQR) and deviation of RM 47 (MAD) suggest moderate price variations reflecting different property features.
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.