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All Journal Jupiter PROtek : Jurnal Ilmiah Teknik Elektro Jurnal Obsesi: Jurnal Pendidikan Anak Usia Dini Jurnal Ilmiah FIFO Jurnal TAM (Technology Acceptance Model) Prosiding Seminar Nasional Darmajaya KACANEGARA Jurnal Pengabdian pada Masyarakat Jurnal Informasi dan Komputer Jurnal Teknologi Terpadu Jurnal ICT : Information Communication & Technology Aisyah Journal of Informatics and Electrical Engineering Abdimas Universal BERNAS: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika (JUTIF) Jurnal Pengabdian Kepada Masyarakat Ungu ( Abdi Ke Ungu) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Metta : Jurnal Ilmu Multidisiplin Journal of Information Systems and Technology Research Jurnal Algoritma Jurnal Masyarakat Madani Indonesia Dikdimas : Jurnal Pengabdian Kepada Masyarakat IJOEM: Indonesian Journal of Elearning and Multimedia Finger : Jurnal Ilmiah Teknologi Pendidikan Jurnal Informatika Polinema (JIP) Jurnal Pendidikan Teknologi Informasi dan Komunikasi Jurnal Rekayasa Perangkat Lunak Jurnal TAM (Technology Acceptance Model)
Nur Aminudin
Universtitas Aisyah Pringsewu
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Design and Evaluation of AI-Enhanced Multimedia Learning Systems: Usability, Accessibility, and Engagement in Broadband-Based Online Education Ikna Awaliyani; Dita Septasari; Nur Aminudin; Septika Ariyanti
IJOEM: Indonesian Journal of E-learning and Multimedia Vol. 5 No. 2 (2026): Indonesian Journal of E-learning and Multimedia
Publisher : CV. Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijoem.v5i2.573

Abstract

Background: Artificial intelligence (AI) has increasingly been integrated into multimedia learning environments to support personalization, accessibility, and learner engagement in broadband-based online education. However, many existing systems still evaluate these dimensions separately, which limits their overall effectiveness and scalability.Aims: This study aims to design and empirically evaluate an AI-enhanced multimedia learning system using a unified evaluation framework that integrates system performance, usability, accessibility, and learner engagement within broadband-based higher education contexts.Methods: An explanatory sequential mixed-methods design was employed, involving quantitative analysis with 150 students and qualitative exploration with 12 participants. Data were collected through system performance logs, System Usability Scale (SUS) assessments, WCAG 2.1–based accessibility evaluations, and learner engagement metrics.Results: The findings indicate that AI-driven adaptivity improves system responsiveness, achieves high usability, supports digital accessibility, and enhances learner engagement in broadband-based learning environments. The results demonstrate the effectiveness of the system across technical, experiential, and behavioral dimensions.Conclusion: The key contribution of this study lies in proposing and validating an integrated evaluation framework that holistically captures the performance and user experience of AI-enhanced multimedia learning systems, an area that has been underexplored in prior research. These findings provide important theoretical and practical implications for the design of inclusive, adaptive, and user-centered online learning platforms.
Predicting Consumer Purchasing Behavior Using Random Forest on Retail Transaction Data Ningsiah Ningsiah; Nur Aminudin
Jurnal Ilmiah FIFO Vol. 18 No. 1 (2026)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/fifo.2026.v18i1.002

Abstract

The rapid digital transformation in the retail sector has generated massive volumes of consumer transaction data stored within retail information systems. Although these data hold strategic value for decision-making, their utilization often remains limited to descriptive reporting. This study aims to analyze and predict consumer purchasing behavior by integrating machine learning–based predictive analytics into retail information systems using the Kaggle retail transaction dataset. The research methodology includes data preprocessing, exploratory data analysis, feature selection, and predictive model development using logistic regression, decision tree, and random forest algorithms. Model performance was evaluated using accuracy, precision, recall, and ROC–AUC metrics. The results indicate that the random forest model outperformed the other algorithms, achieving an accuracy of 88.76%, precision of 87.92%, and recall of 86.48%, demonstrating superior discriminative capability. These findings confirm that ensemble-based learning methods effectively capture complex and non-linear consumer purchasing patterns. The study contributes theoretically by extending the role of retail information systems from descriptive reporting tools to predictive decision-support systems, while practically providing a robust analytical framework to support inventory optimization, targeted promotion strategies, and personalized service delivery in data-driven retail environments.
An Intelligence-Oriented System Architecture for Integrated Pharmaceutical Data Analytics and Decision Support Ningsiah; Nur Aminudin; Septika Ariyanti; Ramil Abbasov
Journal of Information Systems and Technology Research Vol. 5 No. 1 (2026): January 2026
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v5i1.1461

Abstract

This study proposes and evaluates an intelligence-oriented hybrid information system architecture for pharmaceutical data analytics and decision support. Unlike conventional approaches that treat analytics as an external component, the proposed framework embeds analytical intelligence directly into the core system architecture through an integrated, multi-layer design. The study adopts an experimental and system development methodology using a large-scale public pharmaceutical dataset consisting of 240,591 records and 10 attributes. Supervised machine learning models are implemented to support data classification and intelligence generation, and system performance is evaluated using accuracy, precision, recall, and F1-score. The results demonstrate that the proposed hybrid system consistently outperforms baseline and non-integrated approaches, achieving higher predictive stability and analytical consistency. The main contribution of this study lies in its system-level integration model, which enables the transformation of raw pharmaceutical data into actionable decision-support intelligence. The findings confirm that embedding analytics within information system architecture significantly enhances both analytical performance and decision-making capability in pharmaceutical information systems.
Co-Authors -, Nungsiyati Abdullah Umar Faqih Al Ikhsani Adi Prasetia Nanda Afandi, Asep Afanto, Hendri Afnan Zalfa Salsabila A Afrianto, Rifki Agus Wantoro Ahmad Ahlun Nazar Al Farisi, Muhammad Farhan Alfina Alfina Andika, Tahta Herdian Andino Maseleno Aprilia, Fenny Ariyanti, Septika Aviv Fitria Yulia Ayu Andini, Dwi Yana Bagus Wicaksono, Setepanus Bastian, Arif Alexander Bintoro, Panji Boris Brahmono Cahyadi, Septian Damayanti Abdul Karim, Dewi Desni Sagita, Yona Dikpride Despa Dita Septasari Dwi AD Putra Dwi Feriyanto Dwi Yana Ayu Andini Dwi Yana Ayu Andini Efendi, Dwi Marisa Eko Setiawan, Agustinus El Hanif, Azka Fadzlan Thoriq Fahlul Rizki Fandi Ahmad Ferly Ardhi Ferly Ardhy Fiqih Satria Fitra Endi Fernanda, Fitra Endi Habib, Cahya Hasanah, Khuswatun Ida Ayu Puspita Sari Ikna Awaliyani Ilham Ubaidillah Inti Barokah Amaliah Irwan Susilo Khuswatun Hasanah Luthfia B, Yessiana M. Islamahdi Marsim, Etanaulia MARTHALENA, YENNY Mayang Indah Sari Mitha Franciska Muhammad Kristiawan Muhammad, Adamu Abubakar Muharni, Sita Mukaromah, Hafsah Mutmainah Mutmainah Naufal Sinatria Ningsiah Nugroho, Tri Adi Nungsiyati Nungsiyati Nurul Hidayat Nurul Isti Fada Ockhy Jey Fhiter Wassalam Pradana, Alfazri Putra Putra, Dwi AD Ramadhanti, Dinda Ramil Abbasov Ratnasari Ratnasari Rendy Yudha Pratama Rian Candra Pratama Rimanto, Rimanto Rini Wahyuni Rizki, Fahlul Rohmah, Nurbaiti Rustam Rustam Salman Alfarisi Salimu Salman Alfarisi Salimu Salsabila A, Afnan Zalfa Satria, Fiqih Septika Yani Veronica Setiawan, Susilo Setiyarini, Elita Yuni Shima Asadi Sigit Andriyanto Sukamto, Anton Sumerti, Ela Tahta Herdian Andika Taufik Rahman Taufiq Taufiq Ulfa Isni Kurnia Usmanto, Budi Wicaksono, Garda Arif Wina Safutri Yani Veronica, Septika Yovita, Rizka Dwi Zalfa Salsabila A, Afnan Zulkifli Zulkifli Zulkifli