| Price | PSF | Size | Date | Type |
|---|
|
RM200,000
|
RM81
|
2,465 sqft
|
|
|
|
RM183,000
|
RM74
|
2,465 sqft
|
|
|
|
RM150,000
|
RM61
|
2,465 sqft
|
|
|
|
RM200,000
|
RM81
|
2,465 sqft
|
|
|
|
RM220,000
|
RM89
|
2,465 sqft
|
|
|
|
RM195,000
|
RM79
|
2,465 sqft
|
|
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Nearby areas in Ulu Kinta
Bandar Baru Sri Klebang
Panorama Lapangan Perdana
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Taman Kinding Flora
Taman Cempaka
Bandar Baru Lapangan
Taman Klebang Putra
Bandar Seri Botani
Taman Polo Laguna @ Tambun
Taman Desa Lang Indah
Medan Klebang Restu
Taman Pertama (Silibin)
Taman Medan Lapangan Mulia
PSF median price per sq ft · 12m its change over the past 12 months
Most-traded areas in this mukim, by number of recorded subsale transactions. See every area in Ulu Kinta
Market Snapshot
CommercialRM189,000
RM135 psfMedian transaction price
Taman Medan Lapangan Mulia in Kinta, Perak recorded 12 subsale transactions between 2021 and 2026, with a median price of RM189K and a median price per square foot (PSF) of RM79.
This area consists exclusively of commercial properties, with no residential listings recorded.
Price remained flat, and PSF growth was PSF remained flat. The median price is RM189K, with most transactions falling within a stable range of RM144K to RM234K, and a typical market range of RM155K to RM223K.
Most transactions involved 2 - 2 1/2 storey shop, though some variety exists in the market.
Price per square foot shows a median of RM79, though individual units vary from RM47 to RM111 in the core range. The broader market spans RM54.99 to RM103.24, indicating diverse property characteristics. A wider spread (IQR: RM48.25) and deviation (MAD: RM32) indicate significant PSF variations, likely due to diverse property types or conditions.
While the area has shown positive growth trends, price variations suggest a more dynamic market. This presents opportunities for investors comfortable with moderate volatility. Significant price variations suggest comparing multiple properties and timing the market carefully. Limited transaction history suggests carefully evaluating comparable sales data.