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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Journal of Education and Learning (EduLearn) Insight: Jurnal Ilmiah Psikologi
Saad, Aslina
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Humanities Computer Science & IT Education Engineering Library & Information Science Social Sciences Other

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A systematic review on research trends, datasets, algorithms, and frameworks of children’s nutritional status prediction Swastina, Liliana; Rahmatullah, Bahbibi; Saad, Aslina; Khan, Hussin
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp1868-1877

Abstract

The monitoring of children's nutritional status serves as a crucial tool for assessing the health of both children and society as a whole. In this regard, machine learning has been employed to predict nutritional status for monitoring purposes. This topic has been extensively discussed; however, the question remains as to which algorithm or machine learning framework can yield the highest accuracy in predicting the nutritional status of children within a specific region. Furthermore, determining the appropriate dataset for predictions is also crucial. Therefore, this review aims to identify and analyze the research trends, dataset characteristics, algorithms, and frameworks utilized in studies pertaining to the nutritional status of children under the age of five from 2017 to early 2022. The selected papers focus on the application of machine learning techniques in predicting nutritional status. The findings of this research reveal that the Bangladesh DHS 2014 dataset is among the popular choices for machine learning applications in this field. The most commonly employed algorithms include Neural Networks, Random Forests, Logistic Regression, and Decision Trees which demonstrated promising performance. Lastly, the data preprocessing stage within a framework plays a significant role in models aimed at predicting nutritional status.
A systematic review of students’ awareness on cyberbullying at high school level of education Raja Hassan, Raja Muhammad Faiz; Rahmatullah, Bahbibi; Saad, Aslina; Tareq, Ziadoon
Insight: Jurnal Ilmiah Psikologi Vol. 24 No. 1 (2022): FEBRUARY 2022
Publisher : Universitas Mercu Buana Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26486/psikologi.v24i1.1978

Abstract

Today's cyber world is becoming more accessible to anyone. Lack of education and awareness related to cyber security including bullying has contributed to the misuse of available facilities, especially social media. Cyberbullying is a serious concern among secondary students, and owing to the pandemic COVID-19, the majority of secondary students are required to attend class online in order to complete their studies. However, the use of technology in secondary school has a detrimental influence, as seen by the rise in cyberbullying instances among secondary pupils. Using the Scopus database, we discovered 36 publications connected to the term that was used. Following the screening, a total of 17 academic documents that are entirely connected to the study issue were obtained and examined. Thematic analysis performed shows several important aspects studied which looks at the impact, prevention, and knowledge of cyberbullying among secondary students, teachers, and parents. The findings also point towards raising awareness about the impact of cyberbullying on secondary students and how to prevent it. The goal of this systematic literature review is to raise awareness regarding cyberbullying's impact on high school or secondary level students.
Integrating computational thinking into English writing: development of a computational thinking-integrated module Saad, Aslina; Hashim, Haslinda; Rahmatullah, Bahbibi
Journal of Education and Learning (EduLearn) Vol 20, No 1: February 2026
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/edulearn.v20i1.23260

Abstract

This study addresses challenges in teaching English writing skills in English as a second language (ESL) classrooms, proposing a novel approach through computational thinking (CT). A CT-integrated writing module was developed for primary school ESL teachers using the analysis, design, development, implementation, and evaluation (ADDIE) model and qualitative research. Incorporating constructivist and experiential learning theories, the module uses visualization tools like circle maps and flow maps across 8 units, combined with an inquiry-based approach, scaffolding, and localized materials. The 5 CT elements-decomposition, pattern recognition, abstraction, algorithmic thinking and logical reasoning-are embedded to enhance learning. Focus group interviews with 4 ESL experts indicate strong acceptance, highlighting the module’s usability, content, and teaching activities. The study provides a framework for CT-based instructional modules to improve problem-solving and cooperative learning in English writing education.
Co-Authors Hashim, Haslinda Khan, Hussin Liliana Swastina Rahmatullah, Bahbibi Raja Hassan, Raja Muhammad Faiz Tareq, Ziadoon