Taman Sejati Indah 3(B) 1

Kedah, Kuala Muda, Sungai Pasir

Property Transactions

7 subsales grouped by size · 2-Sty Terrace →

Period
transactions middle 50% (P25–P75)
1,300 sqft
Terrace
RM280,000
Lorong 28
1,302 sqft · RM215 PSF
1,350 sqft
2-Sty Terrace
RM280,000
Lorong 26
1,345 sqft · RM208 PSF
RM200,000
Lorong 22
1,345 sqft · RM149 PSF
RM250,000
Lorong Sejati 22
1,345 sqft · RM186 PSF
RM290,000
Jalan Indah 26
1,345 sqft · RM216 PSF
RM270,000
Jalan Indah 6
1,345 sqft · RM201 PSF
2,500 sqft
Terrace
RM250,000
Lorong 30
2,486 sqft · RM101 PSF
Legend Recent Highest Price Highest PSF

Selling in Taman Sejati Indah 3(B) 1? Homes here sold for a median of RM270,000.

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Market Snapshot

Residential

RM270,000

RM207 psf

Median transaction price

Taman Sejati Indah 3(B) 1
© OpenStreetMap · CARTO

Taman Sejati Indah 3(B) 1, Kuala Muda, Kedah

Taman Sejati Indah 3(B) 1 in Kuala Muda, Kedah recorded 7 subsale transactions between 2021 and 2026, with a median price of RM270K and a median price per square foot (PSF) of RM201.

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 RM270K, with most transactions falling within a stable range of RM250K to RM290K, and a typical market range of RM255K to RM285K.

Most transactions involved 2 - 2 1/2 storey terraced, though some variety exists in the market.

For price per square foot, the median is RM201, with most transactions between RM186 and RM216. The usual range is RM179.67 to RM221.67, showing that most units are priced quite close to each other. A typical spread (IQR) of RM42.00 and an average deviation (MAD) of RM15 indicate a highly stable PSF trend across properties.

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.