Binjai Rendah

1, Jalan Taman PAKR, bukit che nik binjai rendah, 21400 Bukit Payong, Terengganu, Malaysia

Property Transactions

4 subsales found

Price Size
Period
transactions middle 50% (P25–P75)
RM250,000
Off Jalan Bukit Payung - Rawai
1,302 sqft RM192 PSF
RM295,000
Off Jalan Binjai Rendah/Rawai (P/L:6417
2,314 sqft RM127 PSF
RM315,000
Off Jalan Binjai Rendah/Rawai (P/L:6417)
2,303 sqft RM137 PSF
RM320,000
Off Jalan Binjai Rendah/Rawai (P/L:6416)
2,314 sqft RM138 PSF
Legend Recent Highest Price Highest PSF

Selling in Binjai Rendah? Homes here sold for a median of RM305,000.

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Market Snapshot

Residential

RM305,000

RM138 psf

Median transaction price

Binjai Rendah
© OpenStreetMap · CARTO

1, Jalan Taman PAKR, bukit che nik binjai rendah, 21400 Bukit Payong, Terengganu, Malaysia

Maps

Binjai Rendah in Marang, Terengganu recorded 4 subsale transactions between 2021 and 2026, sized between 1,000 and 3,000 sqft, with a median price of RM305K and a median price per square foot (PSF) of RM138.

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 RM305K, with most transactions falling within a stable range of RM277K to RM320K, and a typical market range of RM265K to RM320K.

Most transactions involved 1 - 1 1/2 storey semi-detached, with moderate diversity in property types available.

The median PSF stands at RM138, with core pricing between RM112 and RM163. Market pricing typically extends from RM128.01 to RM147.01, reflecting moderate variation in unit pricing. The spread of RM19.00 (IQR) and deviation of RM25 (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. Despite diverse property types, prices remain relatively stable, offering options for different buyer preferences. Limited transaction history suggests carefully evaluating comparable sales data.