Taman Selayang Indah

9, Jalan Selayang Indah, Taman Selayang Indah, 13020 Butterworth, Pulau Pinang, Malaysia

Property Transactions

6 subsales grouped by size · Bungalow →

Period
transactions middle 50% (P25–P75)
1,450 sqft
2-Sty Terrace
RM668,000
Jalan Selayang Indah 8
1,475 sqft · RM453 PSF
2,850 sqft
Semi-D
RM1,400,000
Lintang Selayang Indah
2,842 sqft · RM493 PSF
3,200 sqft
Bungalow
RM1,970,000
Lintang Selayang Indah
3,218 sqft · RM612 PSF
RM1,627,000
Lintang Selayang Indah
3,208 sqft · RM507 PSF
RM1,600,000
Lintang Selayang Indah
3,208 sqft · RM499 PSF
5,000 sqft
Bungalow
RM1,600,000
Lintang Selayang Indah
5,005 sqft · RM320 PSF
Legend Recent Highest Price Highest PSF

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9, Jalan Selayang Indah, Taman Selayang Indah, 13020 Butterworth, Pulau Pinang, Malaysia

Maps

Taman Selayang Indah in Seberang Perai Utara, Penang recorded 6 subsale transactions between 2021 and 2026, with a median price of RM1.60 million and a median price per square foot (PSF) of RM499.

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 RM1.60 million, with most transactions falling within a stable range of RM1.49 million to RM1.71 million, and a typical market range of RM1.51 million to RM1.69 million.

Most transactions involved detached, with moderate diversity in property types available.

For price per square foot, the median is RM499, with most transactions between RM471 and RM527. The usual range is RM476.81 to RM520.81, showing that most units are priced quite close to each other. A typical spread (IQR) of RM44.00 and an average deviation (MAD) of RM28 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. Despite diverse property types, prices remain relatively stable, offering options for different buyer preferences. Limited transaction history suggests carefully evaluating comparable sales data.