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All Journal Jurnal Ruas (Review of Urbanism and Architectural Studies) Intelektualita Phi : Jurnal Pendidikan Fisika dan Terapan ORBITA: Jurnal Pendidikan dan Ilmu Fisika Journal of Architectural Research and Education INDRA: Jurnal Pengabdian kepada Masyarakat JURNAL ILMU DAN TEKNOLOGI KESEHATAN TERPADU Jurnal Ilmiah Mahasiswa Arsitektur dan Perencanaan Journal of Health Sciences and Epidemiology Leuser Journal of Environmental Studies Journal of Educational Management and Learning Jurnal RAUT Seumike : Society Progress Journal
Zahriah, Zahriah
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Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Journal : Journal of Educational Management and Learning

 1 
Does Online Education Make Students Happy? Insights from Exploratory Data Analysis Noviandy, Teuku Rizky; Idroes, Ghalieb Mutig; Hardi, Irsan; Emran, Talha Bin; Zahriah, Zahriah; Rahimah, Souvia; Lala, Andi; Idroes, Rinaldi
Journal of Educational Management and Learning Vol. 1 No. 2 (2023): December 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/jeml.v1i2.124

Abstract

This study investigates the impact of online education on student happiness. Utilizing a dataset of 5715 students sourced from Bangladesh, we employed an exploratory data analysis to analyze the quantitative data. The key finding is that there is a prevalent trend of dissatisfaction with online education among Bangladeshi students, regardless of demographic factors like age, gender, education level, preferred device for access, or type of academic institution. The dissatisfaction trend highlights the need of continuous improvements and targeted interventions are essential to ensure online education not only enables academic success, but also supports the overall wellbeing and happiness of students in the context of a developing country.
Digital Transformations in Vocational High School: A Case Study of Management Information System Implementation in Banda Aceh, Indonesia Idroes, Rinaldi; Subianto, Muhammad; Zahriah, Zahriah; Afidh, Razief Perucha Fauzie; Irvanizam, Irvanizam; Noviandy, Teuku Rizky; Sugara, Dimas Rendy; Mursyida, Waliam; Zhilalmuhana, Teuku; Idroes, Ghalieb Mutig; Maulana, Aga; Nurleila, Nurleila; Sufriani, Sufriani
Journal of Educational Management and Learning Vol. 1 No. 2 (2023): December 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/jeml.v1i2.128

Abstract

This study examines the digital transformation in vocational education through the implementation of a Management Information System (MIS) in Banda Aceh, Indonesia. Focused on enhancing educational administration and decision-making, the study provides insightful analysis on the integration of MIS in State Vocational High School (SMK), specifically SMKN 1 and SMKN 3 in Banda Aceh. A purposive sampling method was employed for usability testing. The questionnaire-based usability test revealed high reliability and positive user responses across multiple indicators. Data analysis affirmed the system's high user satisfaction, effectiveness, and ease of use. Despite limitations, the study highlights the significant potential of well-designed MIS in improving operational efficiency and user satisfaction in educational settings. Future research directions include expanding the sample size, conducting longitudinal studies, incorporating qualitative methods, and exploring the impact on educational outcomes, to enhance the generalizability and depth of understanding regarding the role of MIS in education.
Machine Learning for Early Detection of Dropout Risks and Academic Excellence: A Stacked Classifier Approach Noviandy, Teuku Rizky; Zahriah, Zahriah; Yandri, Erkata; Jalil, Zulkarnain; Yusuf, Muhammad; Mohamed Yusof, Nur Intan Saidaah; Lala, Andi; Idroes, Rinaldi
Journal of Educational Management and Learning Vol. 2 No. 1 (2024): May 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/jeml.v2i1.191

Abstract

Education is important for societal advancement and individual empowerment, providing opportunities, developing essential skills, and breaking cycles of poverty. Nonetheless, the path to educational success is marred by challenges such as achieving academic excellence and preventing student dropouts. Early identification of students at risk of dropping out or those likely to excel academically can significantly enhance educational outcomes through tailored interventions. Traditional methods often fall short in precision and foresight for effective early detection. While previous studies have utilized machine learning to predict student performance, the potential for more sophisticated ensemble methods, such as stacked classifiers, remains largely untapped in educational contexts. This study develops a stacked classifier integrating the predictive strengths of LightGBM, Random Forest, and logistic regression. The model achieved an accuracy of 80.23%, with precision, recall, and F1-score of 79.09%, 80.23%, and 79.20%, respectively, surpassing the performance of the individual models tested. These results underscore the stacked classifier's enhanced predictive capability and transformative potential in educational settings. By accurately identifying students at risk and those likely to achieve academic excellence early, educational institutions can better allocate resources and design targeted interventions. This approach optimizes educational outcomes and supports informed policymaking, fostering environments conducive to student success.
Development of a Web-Based Educational Management System for a Technology Vocational High School in Banda Aceh, Indonesia Idroes, Rinaldi; Afidh, Razief Perucha Fauzie; Zahriah, Zahriah; Noviandy, Teuku Rizky; Sugara, Dimas Rendy; Ahsya, Yahdina; Amirah, Kelsy; Baihaqi, Baihaqi; Dharma, Aditia
Journal of Educational Management and Learning Vol. 2 No. 2 (2024): November 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/jeml.v2i2.230

Abstract

This study explores developing and implementing a web-based Management Information System (MIS) tailored for SMK Negeri 2 Banda Aceh, a vocational school in Indonesia. To enhance administrative efficiency and address unique challenges in vocational education, the system centralizes tasks such as attendance tracking, academic record management, and internship coordination. Employing the waterfall model, this project proceeded through structured phases, including requirements analysis, system design, development, and usability testing. A sample of 50 users, comprising students, teachers, and school operators, evaluated the system based on usability, interface design, and information clarity through a questionnaire, yielding high satisfaction scores. Reliability testing and correlation analysis revealed strong internal consistency across questionnaire items and identified critical factors influencing user satisfaction, such as interface appeal and effective error resolution. The results indicate that the system meets core user needs and contributes to a streamlined, user-friendly school management process. With implementation planning, user training, and ongoing maintenance, this MIS offers a sustainable solution that can serve as a model for vocational schools across Indonesia, showcasing the potential of digital solutions in advancing educational administration and supporting career readiness in vocational education.
Embrace, Don’t Avoid: Reimagining Higher Education with Generative Artificial Intelligence Noviandy, Teuku Rizky; Maulana, Aga; Idroes, Ghazi Mauer; Zahriah, Zahriah; Paristiowati, Maria; Emran, Talha Bin; Ilyas, Mukhlisuddin; Idroes, Rinaldi
Journal of Educational Management and Learning Vol. 2 No. 2 (2024): November 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/jeml.v2i2.233

Abstract

This paper explores the potential of generative artificial intelligence (AI) to transform higher education. Generative AI is a technology that can create new content, like text, images, and code, by learning patterns from existing data. As generative AI tools become more popular, there is growing interest in how AI can improve teaching, learning, and research. Higher education faces many challenges, such as meeting diverse learning needs and preparing students for fast-changing careers. Generative AI offers solutions by personalizing learning experiences, making education more engaging, and supporting skill development through adaptive content. It can also help researchers by automating tasks like data analysis and hypothesis generation, making research faster and more efficient. Moreover, generative AI can streamline administrative tasks, improving efficiency across institutions. However, using AI also raises concerns about privacy, bias, academic integrity, and equal access. To address these issues, institutions must establish clear ethical guidelines, ensure data security, and promote fairness in AI use. Training for faculty and AI literacy for students are essential to maximize benefits while minimizing risks. The paper suggests a strategic framework for integrating AI in higher education, focusing on infrastructure, ethical practices, and continuous learning. By adopting AI responsibly, higher education can become more inclusive, engaging, and practical, preparing students for the demands of a technology-driven world.
Co-Authors Abd Rahman, Sunarti Afidh, Razief Perucha Fauzie Ahmad, Nur Hidayah Binti Ahsya, Yahdina Akbar, Zulhiddin Alaidin, Samsul Fala Amir, Diva Kanasya Amirah, Kelsy Ammalia, Nur Rizka Arani, Lidia Sartika Dharma, Aditia Dyah Erti Idawati, Dyah Erti Editya, Muhammad Heru Arie Eko Suhartono Emran, Talha Bin Fahira, Adinda Farisa Sabila Fera, Annisa Ghazi Mauer Idroes Hadi Kurniawan, Hadi Hanan, Dafif Hardi, Irsan Hermaniati, Dwiana Hilal, Iin Shabrina Husnul Khatimah Ida Meutiawati Idroes, Ghalieb Mutig Irfandi Irfandi, Irfandi Irvanizam, Irvanizam Irzaidi, Irzaidi Juniar Afrida Khairan Khairan Kusumo, Fitranto Lala, Andi Lana Sari Lanaya, Dela Mahmud, Mirza Maria Paristiowati Maulana, Aga Mawaddah, Siti Afifah Mohamed Yusof, Nur Intan Saidaah Muhammad Subianto Muhammad Yusuf Mukhlisuddin Ilyas Muliadi Mursyida, Waliam Muslem Muslem, Muslem Nurleila, Nurleila Nursaniah, Cut Purba, Ratih Puspita Kusumadewi Qalbi, Zahwatun Haninul Rahmati Rahmati Ramadani, Dinda Ramadhini, Dhita Razief Perucha Fauzie Afidh Rinaldi Idroes Riza Priandi Salsabila, Athaya Sari, Lana Sasmita, Novi Reandy Shalehah, Shalehah siti hanisah Sofyan, Rahmi Souvia Rahimah sufriani, sufriani Sugara, Dimas Rendy Suhendrayatna Suhendrayatna Tarisza, Shubhan Zarkasya Teuku Rizky Noviandy Ulhaq, Muhammad Zia Wulandari, elysa Yandri, Erkata Zahrul Fuadi Zariyana, Zariyana Zhilalmuhana, Teuku Zuchra Helwani, Zuchra Zulkarnain Jalil