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All Journal Journal of Embedded Systems, Security and Intelligent Systems Artificial Intelligence in Educational Decision Sciences Journal of Vocational, Informatics and Computer Education Journal of Applied Artificial Intelligence in Education Journal of Education for Creativity and Innovation
Annajmi Rauf
Universitas Negeri Makassar
Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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AI-Based Educational Decision Analytics: K-Means Clustering of University Students’ Digital Learning Readiness Using Limited and Full Attitude Schemes Annajmi Rauf; Elma Nurjannah; Fredy Ganda Putra; Saipul Abbas
Artificial Intelligence in Educational Decision Sciences Vol 1 No 1 (2026): Artificial Intelligence in Educational Decision Sciences
Publisher : PT. Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/aieds.v1i1.19

Abstract

Purpose – Advancements in digital learning require students to be adequately prepared both psychologically and technologically. However, students’ attitudes toward digital learning have not yet been systematically mapped using data-driven segmentation approaches. This study aims to classify university students based on similarities in their attitudes toward digital learning using the K-Means clustering algorithm and to identify the most influential dimensions distinguishing levels of digital readiness.Methods – This study employed an exploratory quantitative design using survey data collected from 469 university students. Clustering was conducted using the K-Means algorithm implemented in the Orange Data Mining application. Two variable schemes were compared: a limited scheme comprising four constructs (Psychological Traits, Growth Mindset, Learner Motivation & Engagement, and Digital Competence) and a full scheme including six constructs with the addition of Digital Readiness & Mindfulness and Student Satisfaction. Data were normalized using Min–Max normalization, and cluster quality was evaluated using the Silhouette Coefficient.Findings – Results indicate that both schemes consistently produced two optimal clusters representing students with high and low levels of digital learning readiness. The highest Silhouette Coefficient values were obtained at K = 2 for both schemes (0.335 for the limited scheme and 0.323 for the full scheme). Psychological Traits and Learner Motivation & Engagement emerged as the most significant differentiating dimensions between clusters, followed by Digital Competence.Research limitations – The findings are limited to self-reported data and a single institutional context, which may constrain generalizability. Additionally, the cross-sectional design does not capture changes in student attitudes over time.Originality – This study contributes a comparative clustering framework that integrates psychological, motivational, and technological dimensions to map digital learning readiness. The results provide a practical foundation for designing adaptive and personalized digital learning strategies based on student readiness profiles.
Analisis Tingkat Penerimaan Mahasiswa terhadap Pembelajaran Online berbasis Gamifikasi Pada Perguruan Tinggi Petrus Jacob Pattiasina; Ilma Wulansari Hasdiansa; Annajmi Rauf; Nur Alamsyah; Sulpiani; Siti Auliyani Saleh
Journal of Vocational, Informatics and Computer Education Vol 2, No 1 (2024): Juni 2024
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/voice.v2i1.24

Abstract

Pembelajaran daring sering kali menghadapi tantangan terkait motivasi dan keterlibatan mahasiswa. Tujuan penelitian ini adalah untuk menganalisis tingkat penerimaan mahasiswa terhadap pembelajaran daring berbasis gamifikasi. Penelitian ini menggunakan metode kuantitatif dengan desain cross-sectional, mengumpulkan data melalui kuesioner dari 64 responden. Hasil penelitian menunjukkan bahwa elemen gamifikasi, khususnya aspek philanthropist dan socializer, memberikan dampak terbesar terhadap motivasi dan partisipasi mahasiswa dengan nilai rata-rata 3,96 dan 3,9. Sebaliknya, aspek achiever dan explorer memiliki pengaruh yang lebih kecil. Penelitian ini menyimpulkan bahwa penerapan gamifikasi dapat meningkatkan keterlibatan mahasiswa dalam pembelajaran daring, dan menyarankan penelitian lebih lanjut untuk mengeksplorasi faktor-faktor individu yang mempengaruhi penerimaan gamifikasi.
Analisis Pengaruh Chatbot AI terhadap Pengalaman Mahasiswa Menggunakan E-commerce Israwati Hamsar; Nur Febrianti; Amelia Uswatun Khasanah; Annajmi Rauf; Elma Nurjannah
Journal of Vocational, Informatics and Computer Education Vol 2, No 2 (2024): December 2024
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/voice.v2i2.20247

Abstract

As e-commerce platforms increasingly adopt AI technologies, the effectiveness of chatbot integration in enhancing user experience among students remains underexplored. This study aims to analyze the impact of AI-powered chatbots on the shopping experience of university students in Makassar. Using a quantitative approach, data were collected via structured questionnaires from 88 student respondents and analyzed through descriptive and inferential methods. The findings reveal that students perceived the chatbot as highly capable of solving complex inquiries, offering relevant solutions, and delivering efficient service. The chatbot's responsiveness and ease of use received high average scores, indicating strong user satisfaction. Furthermore, the chatbot positively influenced customer satisfaction, including increased purchase intention and likelihood to recommend. These results suggest that AI chatbots significantly contribute to enhancing service quality in e-commerce and should be strategically utilized to meet the expectations of young digital consumers.
AI Hallucinations in AI-Assisted Educational Decision-Making and Academic Honesty Intentions Among Undergraduates Desitha Cahya; Putri Ramdani; Annajmi Rauf; Andi Baso Kaswar; M Miftach Fakhri
Journal of Applied Artificial Intelligence in Education Vol 1, No 2 (2026): January 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/jaaie.v1i2.9

Abstract

Artificial Intelligence in Education (AIED) is increasingly used to improve learning efficiency, personalization, and academic productivity. however, persistent risks such as AI hallucinations, algorithmic bias, and limited transparency can undermine the reliability of AI outputs and create ethical vulnerabilities that threaten academic integrity. This study aims to examine how students’ perceptions of algorithmic bias, perceived transparency of AI systems, and digital literacy influence their intentions to behave honestly when using AI for academic purposes. A quantitative cross-sectional survey was administered to 97 undergraduate students with experience using generative AI tools, and the proposed relationships were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4. The results indicate that algorithmic bias (β = 0.248; t = 2.420; p = 0.008), transparency (β = 0.188; t = 1.920; p < 0.001), and digital literacy (β = 0.499; t = 5.457; p = 0.027) each have positive and significant effects on honest behavior intentions, with digital literacy emerging as the strongest predictor. These findings imply that strengthening students’ digital literacy together with institutional efforts to promote transparent and fairness-aware AI use can reduce unethical practices and foster a more integrity-centered academic environment in AI-assisted learning, while also informing ethical behavior frameworks for AIED implementation in higher education.
Dukungan Sistem dan Model Gamifikasi Untuk Meningkatkan Partisipasi Actor dalam Lingkungan E-learning Annisa Soedali Putri; Diva Armelia; Putwal Arjuna; Annajmi Rauf
Journal of Education for Creativity and Innovation Vol. 1 No. 1 (2025): Agustus
Publisher : PT. Global Research Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Kemajuan teknologi digital telah mendorong perubahan signifikan dalam pendidikan, termasuk pemanfaatan gamifikasi untuk meningkatkan partisipasi dalam e-learning. Penelitian ini bertujuan untuk menganalisis peran sistem dan model gamifikasi dalam mendorong motivasi serta keterlibatan mahasiswa pada lingkungan pembelajaran digital. Metode yang digunakan adalah penelitian kuantitatif dengan desain cross-sectional, melibatkan 35 mahasiswa Jurusan Teknik Informatika yang dipilih sebagai responden melalui kuesioner. Hasil penelitian menunjukkan bahwa penerapan gamifikasi melalui elemen-elemen seperti poin, lencana, dan leaderboard mampu meningkatkan motivasi belajar, partisipasi aktif, serta keterlibatan mahasiswa dalam proses pembelajaran. Kesimpulannya, dukungan sistem e-learning yang terintegrasi dengan gamifikasi memberikan kontribusi penting terhadap efektivitas pembelajaran, serta dapat menjadi strategi yang relevan untuk menggeser pendekatan belajar dari teacher-centered ke student-centered learning.
Development of Cloud-Based Taskify Application For Time Management Nur Fadhylah As; Muh. Rahmat Wahyudi JY; Annajmi Rauf; Pramudya Asoka Syukur; Andi Dio Nurul Awalia; M. Miftach Fakhri
Journal of Embedded Systems, Security and Intelligent Systems Vol 5, No 2 (2024): July 2024
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v5i2.5041

Abstract

In the 21st century digital era, advances in technology and information have developed rapidly, one of which is cloud computing. This study aims to design a cloud-based task management application called TaskIfy using firebase technology and agile methods. TaskIfy was designed to help users manage their time and daily activities more effectively. The Agile method was used in two sprint cycles to ensure iterative development and responsiveness to user feedback. The main features implemented include authentication, task management, search, and calendars. Black box testing was conducted to ensure the functionality of the application. The results showed that TaskIfy successfully improved user efficiency and productivity in managing schedules and completing tasks. However, some additional features have not been developed, such as better calendar integration and collaboration features. Future research can focus on developing these features to optimize the user experience. The main contribution of this research is the implementation of TaskIfy as a practical tool for effective time management, combining cloud computing technology and agile methodology to improve efficiency in everyday life.
StudySync Mobile Application Design for Student Academic Activity Management Based on SQLite Database Arsyanda; M. Miftach Fakhri; Pramudya Asoka Syukur; Devi Miftahul Jannah; Elma Nur Jannah; Annajmi Rauf
Journal of Embedded Systems, Security and Intelligent Systems Vol 5, No 3 (2024): November 2024
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v5i3.5042

Abstract

The development of information and communication technology has made significant contributions in various sectors, including education. Mobile applications have become an effective solution in improving time management and reducing academic procrastination among students. This research aims to design and develop a mobile application called StudySync that utilizes SQLite database to assist students in organizing their academic activities. The development method used is the Agile method with three sprint cycles, ensuring incremental improvements and continuous validation of features. The application offers task management features, note-taking, reminders, and a search system to facilitate the management of academic information. SQLite was chosen as the main database due to its self-contained, serverless, zero-configuration, and transactional nature, suitable for mobile applications that require fast and reliable database access. The test results show that the StudySync application successfully meets the needs of users in organizing academic assignments and notes and improving student time management.
Co-Authors Amelia Uswatun Khasanah Andi Baso Kaswar Andi Dio Nurul Awalia Annisa Soedali Putri Arsyanda Desitha Cahya Devi Miftahul Jannah Diva Armelia Elma Nur Jannah Elma Nurjannah Fredi Ganda Putra Ilma Wulansari Hasdiansa Israwati Hamsar M Miftach Fakhri M. Miftach Fakhri Muh. Rahmat Wahyudi JY Nur Alamsyah Nur Fadhylah As Nur Febrianti Petrus Jacob Pattiasina Pramudya Asoka Syukur Putri Ramdani Putwal Arjuna Saipul Abbas Siti Auliyani Saleh Sulpiani