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Journal of Educational Management and Learning
Published by PT. Heca Sentra Analitika
ISSN : -     EISSN : 30251117     DOI : https://doi.org/10.60084/jeml
Core Subject : Education,
Education Languange, Linguistic, Communication & Media Mathematics Other
Journal of Educational Management and Learning (JEML) is a prestigious peer-reviewed academic publication that focuses on original research articles and review articles in the field of education management and learning. JEML seeks to encourage interdisciplinary research that connects educational theories to practical applications and their impact on society. The scope of the Journal of Educational Management and Learning (JEML) may include, but is not limited to, the following areas: educational leadership and policy development, school governance and administration, curriculum development and assessment, educational technology and digital learning, teacher professional development, organizational behavior in educational institutions, educational innovation and entrepreneurship, quality assurance and accreditation in education, student engagement and motivation, education and social justice
Arjuna Subject : Umum - Umum
Articles 5 Documents
 1 
Search results for , issue "Vol. 1 No. 1 (2023): August 2023" : 5 Documents clear
Optimizing University Admissions: A Machine Learning Perspective Maulana, Aga; Noviandy, Teuku Rizky; Sasmita, Novi Reandy; Paristiowati, Maria; Suhendra, Rivansyah; Yandri, Erkata; Satrio, Justinus; Idroes, Rinaldi
Journal of Educational Management and Learning Vol. 1 No. 1 (2023): August 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/jeml.v1i1.46

Abstract

The university admission process plays a pivotal role in shaping the future of aspiring students. However, traditional methods of admission decisions often fall short in capturing the holistic capabilities of individuals and may introduce bias. This study aims to improve the admission process by developing and evaluating machine learning approach to predict the likelihood of university admission. Using a dataset of previous applicants' information, advanced algorithms such as K-Nearest Neighbors, Random Forest, Support Vector Regression, and XGBoost are employed. These algorithms are applied, and their performance is compared to determine the best model to predict university admission. Among the models evaluated, the Random Forest algorithm emerged as the most reliable and effective in predicting admission outcomes. Through comprehensive analysis and evaluation, the Random Forest model demonstrated its superior performance, consistency, and dependability. The results show the importance of variables such as academic performance and provide insights into the accuracy and reliability of the model. This research has the potential to empower aspiring applicants and bring positive changes to the university admission process.
Interactive Learning for Water Pollution Awareness: A Game-Based Approach Fatimah, Siti; Farida, Ida; Sukmawardani, Yulia
Journal of Educational Management and Learning Vol. 1 No. 1 (2023): August 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/jeml.v1i1.52

Abstract

This research explores the potential of interactive educational games as a tool to enhance environmental literacy, with a specific focus on water pollution issues. The study introduces a designed game encompassing various interactive modules, such as word games, drag-and-drop tasks, multiple-choice questions, evaluations, and an environmental literacy survey. The validation test was carried out by three validators consisting of material expert lecturers and media experts. The average rcount value for validation test results across material aspects, language aspects, and display (media) aspects was calculated as follows: 0.85, 0.92, and 0.84, resulting in an overall rcount value of 0.87. This overall value signifies high validity and strong interpretational significance. Furthermore, the feasibility test was carried out on 15 chemistry education students who had taken environmental chemistry courses. The average rcount of the feasibility test results from all aspects obtained a percentage value of 87%. This study highlights the importance of game design, evaluating long-term impacts, and integrating interactive games into educational curricula.
Augmented Reality and Student Learning: Analysis of Mental Models of Salt Hydrolysis at SMAN 51 Jakarta, Indonesia Umayah, Anisa; Paristiowati, Maria; Dianhar, Hanhan; Hasibuan, Nur Azizah Putri
Journal of Educational Management and Learning Vol. 1 No. 1 (2023): August 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/jeml.v1i1.53

Abstract

This study aimed to ascertain students' mental models while learning about salt hydrolysis through augmented reality (AR). The study comprised 36 participants from Public High School 51 in Jakarta. A descriptive qualitative approach was adopted for this research, employing various data collection methods such as written drawings, interviews, classroom observations, teacher notes, student worksheets, and final tests. In categorizing students' mental models, three main types emerged: scientific, synthetic, and initial mental models. The findings revealed that 7.20% of students fell into the initial mental model category, 53.90% exhibited synthetic mental models, and 38.90% demonstrated scientific mental models. Notably, incorporating AR into salt hydrolysis learning predominantly influenced the development of synthetic mental models. The study's results also indicated that the utilization of AR positively enhanced students' spatial abilities in understanding submicroscopic representations.
Student Perspectives on the Role of Artificial Intelligence in Education: A Survey-Based Analysis Idroes, Ghazi Mauer; Noviandy, Teuku Rizky; Maulana, Aga; Irvanizam, Irvanizam; Jalil, Zulkarnain; Lensoni, Lensoni; Lala, Andi; Abas, Abdul Hawil; Tallei, Trina Ekawati; Idroes, Rinaldi
Journal of Educational Management and Learning Vol. 1 No. 1 (2023): August 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/jeml.v1i1.58

Abstract

Artificial intelligence (AI) has emerged as a powerful technology that has the potential to transform education. This study aims to comprehensively understand students' perspectives on using AI within educational settings to gain insights about the role of AI in education and investigate their perceptions regarding the advantages, challenges, and expectations associated with integrating AI into the learning process. We analyzed the student responses from a survey that targeted students from diverse academic backgrounds and educational levels. The results show that, in general, students have a positive perception of AI and believe AI is beneficial for education. However, they are still concerned about some of the drawbacks of using AI. Therefore, it is necessary to take steps to minimize the negative impact while continuing to take advantage of the advantages of AI in education.
Impact of Teacher Certification on Teacher Motivation and Performance in State Senior High Schools in Ternate City, Indonesia Albaar, Muhammad Ridha; Acim, Acim; Abdullah, Abubakar
Journal of Educational Management and Learning Vol. 1 No. 1 (2023): August 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/jeml.v1i1.59

Abstract

This study aims to analyze the impact of the teacher certification on teacher’s motivation and performance in State High Schools in Ternate City, Indonesia. This study uses a quantitative approach with a survey method. The sample used in this study was 193 teachers who were selected by proportionate random sampling. The data was analyzed using path analysis supported by descriptive statistical analysis. The results indicate that the teacher certification has a direct effect on teacher's motivation and performance. Therefore, improving the application of teacher certification, and achievement motivation can improve performance.

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