Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal Jurnal Penelitian dan Pengkajian Ilmu Pendidikan: e-Saintika
Abd Halim, Nur Syakinah
Unknown Affiliation
Education Mathematics Physics Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Thermal Annealing Surface Modification: Effect on Surface and Performance of Electrospun Nylon 6,6 Nanofiber Membrane for Wastewater Treatment Mohd Asri, Muhammad Amir Nasrin; Abd Halim, Nur Syakinah; Wirzal, Mohd Dzul Hakim; Mohd Yusoff, Abdull Rahim; Bilad, Muhammad Roil
Jurnal Penelitian dan Pengkajian Ilmu Pendidikan: e-Saintika Vol. 5 No. 1: March 2021
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/e-saintika.v5i1.395

Abstract

As the forefront in fiber materials development, electrospun nanofiber membrane (NFM) is potentially reliable for wastewater treatment due to its excellent properties for instance; large surface area, high porosity, tuneable pore size, and has great flux as compared to other conventional membranes. However, fouling issue will lead to degradation of membrane performance. Fouling issue can be alleviated by applying membrane surface modification. In this study, thermal annealing is applied onto nylon 6,6 nanofiber membrane with three different temperatures (60°C, 80°C and 120°C). Results show that annealing causes membrane shrinkage and reduction of membrane fiber diameter where the fiber reduced from 138.5 nm to 108.5 nm when annealed at 120°C. The optimum annealing temperature for the membrane was found to be at 60˚C as the membrane shows the highest flux at 1200 L/m2.h at 75 minutes filtration time and took longer time to get fouled (>75 minutes) compared with un-annealed membrane (55 minutes). Nylon 6,6 nanofiber membrane is also proven to give more than 90% of COD and turbidity rejection.
Generative AI in Science Education: A Learning Revolution or a Threat to Academic Integrity? A Bibliometric Analysis Wirzal, Mohd Dzul Hakim; Md Nordin, Nik Abdul Hadi; Abd Halim, Nur Syakinah; Bustam , Mohamad Azmi
Jurnal Penelitian dan Pengkajian Ilmu Pendidikan: e-Saintika Vol. 8 No. 3: November 2024
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/e-saintika.v8i3.2127

Abstract

The integration of generative artificial intelligence (AI) in Science, Technology, Engineering, and Mathematics (STEM) education presents transformative opportunities alongside significant challenges. This study investigates the dual impact of generative AI on STEM learning outcomes and academic integrity through a comprehensive bibliometric analysis employing co-citation, keyword analysis, and trend mapping. The results reveal that AI tools such as ChatGPT have revolutionized personalized learning by offering tailored feedback, enhancing critical thinking, and improving student engagement. However, these advancements are tempered by concerns over academic misconduct, particularly plagiarism, and the erosion of essential cognitive skills due to overreliance on AI-generated content. Ethical considerations remain critical, necessitating the development of robust policies and ethical frameworks to safeguard academic integrity. Beyond educational settings, the findings suggest broader applicability to professional training and skills development, as the benefits and challenges of AI extend beyond coursework. This research provides valuable insights for educators, policymakers, and researchers, advocating for a balanced approach to AI integration that maximizes its potential while preserving educational standards.
Co-Authors Abdull Rahim Mohd Yusoff Bilad, Muhammad Roil Bustam , Mohamad Azmi Md Nordin, Nik Abdul Hadi Mohd Asri, Muhammad Amir Nasrin Wirzal, Mohd Dzul Hakim