PCA and logistic regression model classifies Razorback Sucker habitats with 70% accuracy using stable isotopes, aiding conservation efforts.

As Kuala Lumpur and Selangor continue to develop, they attract many young professionals and individuals from other states seeking better career opportunities. With the rising cost of living—particularly in Kuala Lumpur—renting has become a more practical choice, especially for newcomers to the urban workforce. Proximity to public transport such as LRT, MRT, and KTM is a key factor in rental decisions, helping tenants save on transport costs. Rental prices vary widely depending on location, unit size, furnishing, and amenities. For instance, apartments in Bangsar South typically start from RM2,000 (PropertyGuru, 2024; EdgeProp, 2024). This project analyzes apartment rental listings from mudah.my in Kuala Lumpur and Selangor to uncover key pricing patterns. A regression model will be used to predict rental prices, while a classification model will explore furnishing status based on property features. The findings aim to support better decision-making for both tenants and property owners.

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Quadratic discriminant analysis of fin ray isotopes achieves 87-90% accuracy in classifying hatchery versus wild Razorback Suckers, providing a non-lethal method for conservation monitoring.