Affordable housing especially in a city environment is recognized as one of citizen needs among the mid-dle-income groups. This research paper intended to explore the possibilities to use data mining algorithms: Linear Regression, Random Forest and Gradient Boosting algorithms for predicting and analyzing the housing affordability price for middle-income earners in Petaling Jaya district, Malaysia. The dataset from Malaysia House Index by Petaling Jaya district used to evaluate based on the proposed algorithms. The dataset extracted based on residential property sub-sectors with three attributes. Based on the prediction models, as results, the Gradient Boosting algorithm shows higher accuracy of 74% for predicting affordable housing price in Petaling Jaya district, Malaysia compared to other prediction techniques. Keywords: Affordable housing price; Linear regression; Random forest and gradient boosting..

713 hits

Social entrepreneurship represents a novel methodology for tackling global social issues. Despite increasing global interest, less knowledge exists regarding how social enterprises efficiently utilize the abilities of autistic individuals, especially within the Malaysian context. Therefore, this study aims to investigate the realm of social entrepreneurship in Malaysia and examine how it creates social value for autistic individuals by recognizing the distinct problems they encounter. A qualitative methodology was employed, utilizing data gathered from semi-structured interviews, observations, and documentation. A thematic analysis was performed on data collected from six social enterprises in the Klang Valley that predominantly assist autistic individuals. Findings reveal several key themes, such as high unemployment rates among autistic individuals, pathways to inclusion and empowerment, the existence of support systems, and structural challenges within the social entrepreneurship ec.....

29 hits