Taman Pekatra Indah
15, Jalan Pekatra Indah, Taman Pekatra Indah, 14120 Simpang Ampat, Pulau Pinang, Malaysia
15, Jalan Pekatra Indah, Taman Pekatra Indah, 14120 Simpang Ampat, Pulau Pinang, Malaysia
|
Road
|
Price
|
PSF
|
Size
|
Date
|
Type
|
|---|---|---|---|---|---|
| 2023 | |||||
|
Lorong Pekatra Indah 26
|
RM 280,000
|
RM 142
|
1,970 sqft
|
|
LC House |
| 2022 | |||||
|
Lorong Pekatra Indah 26
|
RM 350,000
|
RM 178
|
1,970 sqft
|
|
Terrace |
|
Lorong Pekatra Indah 25
|
RM 350,000
|
RM 180
|
1,948 sqft
|
|
Terrace |
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Market Snapshot
RM 350,000
RM 178 psfMedian transaction price
RM 280,000
RM 192 psfMedian transaction price
15, Jalan Pekatra Indah, Taman Pekatra Indah, 14120 Simpang Ampat, Pulau Pinang, Malaysia
MapsTaman Pekatra Indah in Seberang Perai Selatan, Penang recorded 3 subsale transactions between 2021 and 2026, sized between 1,925 and 1,974 sqft, with a median price of RM 350K and a median price per square foot (PSF) of RM 178.
This area contains both residential and commercial properties. View 54 residential properties or 14 commercial properties separately for more focused analysis.
Price remained flat, and PSF growth was PSF remained flat. The median price is RM 350K, with most transactions falling within a stable range of RM 317K to RM 350K, and a typical market range of RM 306K to RM 350K.
Most transactions involved 1 - 1 1/2 storey terraced, with high diversity across multiple property types.
For price per square foot, the median is RM 178, with most transactions between RM 160 and RM 195. The usual range is RM 131.31 to RM 224.06, showing that most units are priced quite close to each other. With an IQR of RM 92.75 and MAD of RM 17, 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. Despite diverse property types, prices remain relatively stable, offering options for different buyer preferences. Limited transaction history suggests carefully evaluating comparable sales data.