Basic needs of Universiti Utara Malaysia students

Zakat Allocations and Student Welfare: A comparative study of first-time applicants and repeaters in Malaysia

“…Findings from this study indicated that male students had a higher tendency to allocate zakat funds towards daily expenses such as food and internet services. Previous research has revealed that male students consume three meals per day compared to female students, who typically consume only two meals per day (Ismail, Ahmad, and Enn, 2017). This could potentially be attributed to the limited cooking skills of male students, leading them to eat out more frequently, while female students may save money by cooking at home.…”

“…These are essential needs that must be met for students to be able to focus on their studies without worrying about their basic needs. It is also worth noting that some academic programs require specific uniforms or clothing, such as robes or white coats (Ismail, Ahmad, and Enn, 2017). For example, a law student may need to purchase a robe for their courtroom appearances, which can be quite expensive.…”

“…This raises questions about whether the students were not aware of the available funds or if the allocated funds were not suitable for their needs (Ab Rahmani, 2018;Canggih et al, 2017). The study also found that students' needs and preferences are often difficult to discern and may be influenced by factors such as peer relationships, educational requirements, and cultural differences (Ismail et al, 2017). Therefore, in order to improve the lives of poor undergraduate students, this study aimed to identify their specific needs and categorized them into "first-timers" and "repeaters".…”

Data driven machine learning models for short‐term load forecasting considering electrical vehicle load

“…Time‐series analysis, which has numerical instability, was employed by Tepedino et al, Feinberg and Dora Genethliou, and Koo et al 11‐13 Cheepati and Nageswara Prasad and Atmaca et al 14,15 artificial neural networks were utilized in research work, which needed large volumes of data to train the model and presented challenges in the training of such data. Chen and Chang and Ismail and Mansor 10,16 model of the fuzzy inference system, the selection of the membership function was utilized to create the rule, which was based on trial and error. Support vector machine was employed by Badar and Wu and Shahidehpour 17,18 where selecting the right kernel and issues with its interpretation are of utmost importance.…”

“…Furthermore, Chen and Chang and Tepedino et al, 10,11 used linear regression and multiple linear regression models, which were unreliable for real-time load and unable to manage nonlinear load consumption. Time-series analysis, which has numerical instability, was employed by 10,16 model of the fuzzy inference system, the selection of the membership function was utilized to create the rule, which was based on trial and error. Support vector machine was employed by Badar and Wu and Shahidehpour 17,18 where selecting the right kernel and issues with its interpretation are of utmost importance.…”