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All Journal Journal of Computing Theories and Applications Heca Journal of Applied Sciences Leuser Journal of Environmental Studies Ekonomikalia Journal of Economics Journal of Educational Management and Learning Infolitika Journal of Data Science Indatu Journal of Management and Accounting The International Journal of Financial Systems Grimsa Journal of Business and Economics Studies Journal of Future Artificial Intelligence and Technologies
Idroes, Ghalieb Mutig
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Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Mathematics Medicine & Pharmacology 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.
An Explainable Machine Learning Study of Behavioral and Psychological Determinants of Depression in the Academic Environment Noviandy, Teuku Rizky; Idroes, Ghalieb Mutig; Hardi, Irsan; Ringga, Edi Saputra; Idroes, Rinaldi
Journal of Educational Management and Learning Vol. 3 No. 1 (2025): May 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/jeml.v3i1.304

Abstract

Depression is a significant and growing concern within academic environments, affecting both students and staff due to factors such as academic pressure, financial stress, and lifestyle challenges. This study explores the use of machine learning, specifically a Random Forest classifier, to predict depression risk among students using behavioral, psychological, and demographic data. A dataset of 27,788 student records was analyzed after thorough preprocessing and exploratory data analysis. The model achieved strong performance, with an accuracy of 83.52% and an AUC of 0.91, indicating reliable classification of depression status. Local Interpretable Model-agnostic Explanations (LIME) were employed to enhance interpretability, revealing key predictive features such as suicidal ideation, academic pressure, sleep duration, and dietary habits. These interpretable insights align with existing psychological research and provide actionable information for mental health professionals. The findings highlight the value of explainable AI in educational settings, offering a scalable and transparent approach to early depression detection and intervention. Future work should focus on longitudinal data integration, multimodal inputs, and real-world implementation to strengthen the model’s utility and impact.
Co-Authors Afjal, Mohd Agustina, Maulidar Ali, Najabat Amalina, Faizah Apriliansyah, Feby Attari, Muhammad Umer Quddoos Ayu Puspitasari, Ayu Bani, Nor Yasmin binti Mhd Bruyn, Chané de Chairunnisa, Rizka Çoban, Mustafa Necati Dahlia, Putri Devi, N. Chitra Duwal, Niroj Eddy Gunawan, Eddy Eko Suhartono Emran, Talha Bin Fadila, Sintia Fajri, Irfan Fazli, Qalbin Salim Fijay, Ade Habya Fikri, Mumtaz Kemal Fitriyani Fitriyani Furqan, Nurul Ghazi Mauer Idroes Hadiyani, Rahmilia Hafizah, Iffah Hamaguchi, Yoshihiro Hapzi Ali Hardia, Natasha Athira Keisha Hidayatullah, Ferdy Hironimus Kihwili, Erick HUMAM, RAIS AULIA Idroes, Ghifari Maulana Idroes, Rinadi Iin Shabrina Hilal Irsan Hardi Irvanizam, Irvanizam Isaack Delya, Mussa Kadri, Mirzatul Khairan Khairan Khairul, Mhd Khairun Nisa Kusumo, Fitranto Lala, Andi Majid, M. Shabri Abd Majumder, Shapan Chandra Mardayanti, Ulfa Marsellindo, Rio Maulana, Aga Maulana, Ar Razy Ridha Maulidar, Putri Mirza, Muhammad Alfin Falha Muhammad Subianto Muksalmina Muksalmina Mursyida, Waliam Nghiem, Xuan-Hoa Nurleila, Nurleila Pernici, Andreea Phonna, Rahmatil Adha Prasetio, Rasi Qashmal, Muhammad Ray, Samrat Razief Perucha Fauzie Afidh Rimal Mahdani Rinaldi Idroes Ringga, Edi Saputra Salim Fazli, Qalbin Salimullah, Abul Hasnat Muhammed Saputra, Fachri Eka Saputra, Jumadil Sasmita, Novi Reandy Sikdar, Asaduzzaman Sofyan Syahnur Sofyan, Rahmi Souvia Rahimah Stancu, Stelian sufriani, sufriani Sugara, Dimas Rendy Sugeng Santoso Suhendrayatna Suhendrayatna Suriani Suriani Suwal, Sunil Syahyana, Ahmad T. Zulham Teuku Rizky Noviandy Thahira, Zia Utami, Resty Tamara Wiranatakusuma, Dimas Bagus Zahriah, Zahriah Zhilalmuhana, Teuku Zikra, Naswatun