Taman Pulai Indah

7, Jln Pulai Indah 1, Taman Pulai Indah, 28000 Temerloh, Pahang, Malaysia

Property Transactions

2 subsales found

Price Size
Period
transactions middle 50% (P25–P75)
RM390,000
Jalan Pulai Indah
3,035 sqft RM128 PSF
RM300,000
Jalan Pulai Indah
3,068 sqft RM98 PSF
Legend Recent Highest Price Highest PSF

Selling in Taman Pulai Indah? Homes here sold for a median of RM345,000.

Free to list, about two minutes, and the buyers reading this page will see it.

List your property free

Posts about Taman Pulai Indah

What’s happening in Taman Pulai Indah?

No posts about Taman Pulai Indah yet. Be the first to share what’s happening here.

Market Snapshot

Residential

RM345,000

RM113 psf

Median transaction price

Taman Pulai Indah
© OpenStreetMap · CARTO

Taman Pulai Indah, 7, Jln Pulai Indah 1, Taman Pulai Indah, 28000 Temerloh, Pahang, Malaysia

Maps

Taman Pulai Indah in Temerloh, Pahang recorded 2 subsale transactions between 2021 and 2026, sized between 3,025 and 3,074 sqft, with a median price of RM345K and a median price per square foot (PSF) of RM113.

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 RM345K, with most transactions falling within a stable range of RM300K to RM390K, and a typical market range of RM300K to RM390K.

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

The median PSF stands at RM113, with core pricing between RM98 and RM128. Market pricing typically extends from RM93.90 to RM131.90, reflecting moderate variation in unit pricing. With an IQR of RM38.00 and MAD of RM15, the PSF demonstrates reasonable consistency across the market.

Overall, the market in this area appears stable with consistent appreciation, making it an attractive option for both investors and homebuyers. Moderate price stability provides a balanced market for both buyers and sellers. Limited transaction history suggests carefully evaluating comparable sales data.