Taman Senai Indah

81400 Senai, Johor Darul Ta'zim, Malaysia

Property Transactions

3 subsales grouped by size · Terrace →

Median
RM 300,000
PSF
RM 195
Price Size
1,000 sqft
LC House
RM 150,000
Jalan Indah 2
990 sqft · RM 152 PSF
1,550 sqft
Terrace
RM 400,000
Jalan Indah 1
1,540 sqft · RM 260 PSF
RM 300,000
Jalan Indah
1,539 sqft · RM 195 PSF
Legend Recent Highest Price Highest PSF

Posts about Taman Senai Indah

What’s happening in Taman Senai Indah?

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

Market Snapshot

Residential

RM 300,000

RM 195 psf

Median transaction price

Taman Senai Indah
© OpenStreetMap · CARTO

Taman Senai Indah, 81400 Senai, Johor Darul Ta'zim, Malaysia

Maps

Taman Senai Indah in Kulai, Johor recorded 3 subsale transactions between 2021 and 2026, with a median price of RM 300K and a median price per square foot (PSF) of RM 195.

This area contains both residential and commercial properties. View 10 residential properties or 1 commercial properties separately for more focused analysis.

Price remained flat, and PSF growth was PSF remained flat. The median price is RM 300K, with most transactions falling within a stable range of RM 197K to RM 400K, and a typical market range of RM 238K to RM 363K.

Most transactions involved 1 - 1 1/2 storey terraced, with moderate diversity in property types available.

Price per square foot shows a median of RM 195, though individual units vary from RM 150 to RM 239 in the core range. The broader market spans RM 163.40 to RM 226.40, indicating diverse property characteristics. The spread of RM 63.00 (IQR) and deviation of RM 45 (MAD) suggest moderate price variations reflecting different property features.

While the area has shown positive growth trends, price variations suggest a more dynamic market. This presents opportunities for investors comfortable with moderate volatility. Some price volatility exists, making thorough market research essential before transacting. Limited transaction history suggests carefully evaluating comparable sales data.