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All Journal International Journal of Education, Science, Technology, and Engineering (IJESTE) Indonesian Journal of Electrical Engineering and Computer Science
Lakulu, Muhammad Modi
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Computer Science & IT Education Engineering

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Intention to Use Mobile Learning in Higher Education Institutions: Review Paper Izkair, Ayad Shihan; Lakulu, Muhammad Modi; Mussa, Ibtihal Hassan
International Journal of Education, Science, Technology, and Engineering (IJESTE) Vol 3 No 2 (2020)
Publisher : Lamintang Education and Training Centre, in collaboration with the International Association of Educators, Scientists, Technologists, and Engineers (IA-ESTE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36079/lamintang.ijeste-0302.157

Abstract

Mobile learning is presently taking part in associate degree more and more important role within the instructional method, additionally as within the development of teaching and learning ways for higher education. The power to find out ‘on the go– anytime, anywhere, is changing into more and more fashionable. The advantages offered by mobile learning are important. On the opposite hand, the implementation of mobile learning in educational activity relies on users’ acceptance of technology. Acceptance and intention to use mobile learning may be a topic of growing interest within the field of education. The model of the unified theory of acceptance and use of technology (UTAUT) is planned and developed by researchers via a mixture of eight major theories in activity prediction. UTAUT is among the foremost fashionable and up to date model in information technology acceptance. This is review paper aiming to review UTAUT’s previous studies of intention to use mobile learning. In conclusion, this research provides insight regarding the necessary factors for planning and designing an intention to use mobile learning model in higher education institutions.
A Systematic Review of Mobile-Based Assessment Acceptance Studies from 2009 To 2019 Alrfooh, Ali; Lakulu, Muhammad Modi
International Journal of Education, Science, Technology, and Engineering (IJESTE) Vol 4 No 1 (2021)
Publisher : Lamintang Education and Training Centre, in collaboration with the International Association of Educators, Scientists, Technologists, and Engineers (IA-ESTE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36079/lamintang.ijeste-0401.195

Abstract

Despite many studies being conducted on mobile learning acceptance, few investigate mobile-based assessment acceptance. The objectives of this research are to provide valuable insights into current research on mobile-based assessment literature, and to identify the main gaps in the mobile-based assessment acceptance literature. Therefore, the present study systematically reviews 48 previous studies and eight articles related to mobile-based assessment acceptance to provide a comprehensive analysis of the articles published from 2009 to 2019. Findings indicate that majority of mobile-based assessment studies focused on evaluating the effectiveness and performance of mobile-based assessment system and conducted at the secondary school level. In addition, this study identified several gaps. Further research is needed to study the acceptance problem of a mobile-based assessment system. More investigation is required to predict which external factors that can enhance the acceptance and use of mobile-based assessment among students. The findings of this review study provide a valuable reference for researchers about the current trend of mobile-based assessment research as well as the research gaps that should be covered in future studies.
Proposed model to predict preeclampsia using machine learning approach Aditya Rahman, Raden Topan; Lakulu, Muhammad Modi; Panessai, Ismail Yusuf; Yuandari, Esti; Ulfa, Ika Mardiatul; Ningsih, Fitriani; Tambunan, Lensi Natalia
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp694-702

Abstract

Pregnancy complications, which are the biggest cause of death in productive women, are more common in developing countries with low incomes. One of the contributors to death in pregnant women is preeclampsia which contributes 2-8% every day. Based on research results, more than 70% of the use of technology can be a solution for early prevention in detecting cases of pregnancy. The aim of this research is to build a model for early detection of preeclampsia using a machine learning approach. Sample using retrospective data with sample size 1.473. Based on the result, decision tree (DT) is the best model with accuracy 92.2% (area under curve (AUC): 0.91; Spec: 92.3; and Sens: 83.6), according to weigh correlation we can show 3 (three) highest features causes preeclampsia is history of hypertension, history of diabetes mellitus, and history of preeclampsia. The health of pregnant women is essential in the development of the fetus, so it needs optimal monitoring. Monitoring during pregnancy can now be done through technology-based examinations for assist health workers in making decisions during pregnancy.
Devising the m-learning framework for enhancing students' confidence through expert consensus Sun, Teik Heng; Lakulu, Muhammad Modi; Mohd Noor, Noor Anida Zaria
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i2.pp1035-1052

Abstract

Past research has shown the relationship between self-regulated learning (SRL) and academic success. Self-regulated learners will monitor their learning, reflect on what they have learnt, adjust their learning strategies accordingly, and repeat this entire process throughout their learning. The ability to perform SRL will require the individual to have the belief and confidence in his/her capacity to succeed and accomplish the tasks. Therefore, this study aims to devise a mobile learning (m-learning) framework for enhancing the students’ confidence. To achieve this, the Fuzzy Delphi method was used to validate the proposed framework where the survey questionnaire was distributed to 21 experts who are the experts in their respective fields for their consensus to be obtained. Consensus showed that “assessment data” can indicate the students’ confidence when they attempt the assessment. Experts opined that “goal expectation,” and “viewed lessons, chapters, or syllabus” exert the most influence on the students’ confidence when they attempt their assessment. There was strong consensus from experts that “data security” is the most important element in the system infrastructure, and the “text mining technique” element can be used to evaluate the students’ confidence.
Co-Authors Aditya Rahman, Raden Topan Alrfooh, Ali Esti Yuandari, Esti Ika Mardiatul Ulfa, Ika Mardiatul Izkair, Ayad Shihan Lensi Natalia Tambunan, Lensi Natalia Mohd Noor, Noor Anida Zaria Mussa, Ibtihal Hassan Ningsih, Fitriani Panessai, Ismail Yusuf Sun, Teik Heng