Article Per Year (5 Year)
p-Index From 2021 - 2026
1.628
P-Index
This Author published in this journals
All Journal Information Technology Education Journal 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 Journal of Educational Studies in Science, Technology, Engineering, Arts and Humanities
Nurrahmah Agusnaya
Universitas Negeri Makassar
Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

Published : 11 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 11 Documents
Search

 1   2 
AI-Driven Clustering of Social Media Consumption Patterns and Daily Productivity Using K-Means and DBSCAN in Multigenerational Respondents Nurrahmah Agusnaya; Putri Nirmala; M. Miftach Fakhri; Fadhil Zil Ikram
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.v1i1.8

Abstract

Purpose – The rapid development of digital technology has made social media an integral part of life across generations, yet its intensive use raises growing concerns regarding its impact on daily productivity. This study aims to analyze patterns of social media consumption behavior and their relationship with productivity across age groups using a dual clustering approach based on the K-Means and DBSCAN algorithms.Methods – The study utilizes secondary data from 3,000 multigenerational respondents, processed using Orange Data Mining through stages of data selection, normalization, and unsupervised clustering. K-Means is employed to segment respondents based on proximity to cluster centroids, while DBSCAN is applied to identify density-based behavioral patterns and detect outliers representing extreme digital usage behaviors.Findings – The results indicate that K-Means effectively maps macro-level clusters primarily differentiated by age, achieving an average Silhouette score of 0.537, which reflects stable and well-separated segmentation. In contrast, DBSCAN demonstrates superior capability in identifying micro-level behavioral patterns, particularly respondents exhibiting extreme characteristics such as excessive screen time and non-productive application usage, despite yielding a lower overall Silhouette value. The comparative analysis highlights that K-Means is more suitable for demographic-based segmentation, whereas DBSCAN provides deeper insights into localized and atypical digital behavior.Research limitations – The analysis is based on a randomly sampled subset of a publicly available dataset, which may limit the generalisability of the findings across different cultural, occupational, and socioeconomic contexts. Future studies are encouraged to incorporate longitudinal data and additional behavioral variables to capture temporal dynamics and causal relationships between social media usage and productivity.Originality – This study contributes by systematically comparing centroid-based and density-based clustering approaches within a multigenerational framework to reveal both macro-demographic and micro-behavioral patterns of digital consumption. The proposed dual clustering strategy offers a novel analytical perspective for designing more adaptive and evidence-based digital literacy and productivity enhancement policies.
Skala Literasi AI terhadap Prestasi Belajar Mahasiswa dalam Konteks Pendidikan Level Perguruan tinggi di Era Digital Nurrahmah Agusnaya; Putri Nirmala
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.v2i2.20243

Abstract

Dalam era digital yang terus berkembang, kecerdasan buatan (AI) telah menjadi elemen integral dalam kehidupan sehari-hari. Penelitian ini menyoroti pentingnya literasi AI dengan pendekatan pemahaman konseptual untuk dapat diakses oleh individu dengan berbagai latar belakang studi. Tujuan penelitian ini adalah untuk memahami sejauh mana literasi AI mempengaruhi prestasi belajar mahasiswa di perguruan tinggi. Penelitian ini menggunakan desain penelitian kuantitatif dengan rancangan cross-sectional study. Populasi dan sampel penelitian melibatkan mahasiswa dari berbagai perguruan tinggi di Makassar. Instrumen yang digunakan adalah kuesioner untuk mengumpulkan data mengenai literasi AI dan prestasi belajar mahasiswa. Hasil penelitian menunjukkan bahwa literasi AI memiliki dampak positif terhadap prestasi belajar mahasiswa di berbagai perguruan tinggi. Mahasiswa menunjukkan kenyamanan dan motivasi yang tinggi dalam pengembangan literasi AI, yang berkontribusi pada peningkatan keterlibatan dan interaksi sosial baik dengan sesama mahasiswa maupun dosen. Penelitian ini memberikan kontribusi yang signifikan dalam pengembangan literasi AI di perguruan tinggi. Temuan ini dapat menjadi dasar bagi institusi pendidikan untuk merancang strategi pengembangan literasi AI yang lebih efektif, meningkatkan kualitas pembelajaran, dan memenuhi kebutuhan mahasiswa dalam menghadapi era teknologi AI. Implementasi hasil penelitian ini diharapkan dapat membantu perguruan tinggi untuk mempersiapkan mahasiswa dengan keterampilan yang relevan untuk menghadapi tuntutan dunia kerja yang semakin terkait dengan teknologi AI.
Peran E-Learning dalam Meningkatkan Fleksibilitas dan Prestasi Akademik Mahasiswa: Perspektif dari Kota Makassar Rina Asriani J Tudon B; Nurwahyuni Paallo; Nurrahmah Agusnaya; Fajriani Azis; Andi Anggi Kemalasari
Journal of Vocational, Informatics and Computer Education Vol 3, No 1 (2025): June 2025
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/n2992t13

Abstract

The shift toward digital learning models has raised concerns about students' readiness and their perceptions of e-learning effectiveness in higher education. The aim of this study is to provide a solid foundation for educational institutions, lecturers, and universities in understanding students' awareness levels regarding information technology innovation. This research seeks to explore students' perceptions in Makassar City toward the use of e-learning within blended and online learning models, employing a quantitative approach with a cross-sectional design. The subjects or samples of this study are students from several universities located in Makassar City. The study utilized a questionnaire distributed to students at various universities in Makassar via Google Forms as the data collection instrument. Data analysis was conducted using descriptive statistics and linear regression techniques. The findings indicate that students in Makassar City have a positive perception of e-learning usage in the context of blended and online learning. This perception is based on their experiences in utilizing e-learning within such learning models. The study contributes to a deeper understanding of e-learning implementation in the context of modern education, particularly in efforts to enhance the quality of learning at the higher education level.
Dari Persepsi ke Penerimaan: Analisis TAM terhadap Penggunaan E-Learning di Perguruan Tinggi Makassar M. Andika Aswa; Muhammad Husair Nawawi; Nurrahmah Agusnaya; Rahmawati; Rachmawaty Kadir
Journal of Vocational, Informatics and Computer Education Vol 3, No 1 (2025): June 2025
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/z57qr459

Abstract

The development of digital technology has driven significant changes in learning systems, including the adoption of e-learning in higher education. This study aims to analyze student acceptance of the use of e-learning platforms in Makassar City universities using the Technology Acceptance Model (TAM) framework. The three main constructs analyzed include Perceived Usefulness (PU), Perceived Ease of Use (PEOU), and Attitude Toward Using (ATU). This research uses quantitative approach with survey method, involving 65 students from various study programs who actively participate in online learning. The instrument used was a Google Form-based questionnaire consisting of 15 statements, analyzed using multiple linear regression through Jamovi software. The results showed that PU and PEOU had a positive and significant effect on ATU, with a coefficient of determination (R²) of 0.702. This means that 70.2% of the variation in student attitudes towards e-learning can be explained by these two variables. This finding confirms that perceived usefulness and ease of use are key factors in shaping positive attitudes towards learning technology adoption. This research provides an empirical contribution to the strengthening of the TAM model in the Indonesian higher education context and offers practical recommendations for the development of e-learning systems that are more effective and responsive to user needs.
Student Perceptions of AI in Learning: The Role of Credibility and Emo-tional Well-Being in Supporting Critical Thinking Skills Ummul Khaeri Masna; Arum Putri Rahayu; Sakinah Mawaddah; Nurrahmah Agusnaya; Muh. Yusril Anam
Journal of Applied Artificial Intelligence in Education Vol 1, No 1 (2025): July 2025
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/jaaie.v1i1.3

Abstract

The growing use of artificial intelligence (AI) tools (e.g., ChatGPT, Grammarly) in higher education is often claimed to enhance students’ critical thinking, yet perceived benefits remain inconsistent and may depend more on trust and affective experience than on technical features alone. This study aimed to examine students’ perceptions of AI for supporting critical thinking by testing five predictors—perceived AI credibility, AI quality, cognitive absorption, emotional well-being, and satisfaction—and their effects on overall AI perception. A quantitative cross-sectional survey was administered to 90 Indonesian university students (purposive sampling; ages 18–25) using 26 closed-ended Likert items (5-point scale) and three open-ended questions; data were analyzed in Jamovi using descriptive statistics, Pearson correlations, and multiple linear regression. The results indicated generally moderate perceptions of AI (item means ≈2.2–2.8), significant positive correlations among all variables (p < .001), and strong explanatory power of the regression model (R² = 0.737; adjusted R² = 0.720). In the multivariate model, emotional well-being (β_std = 0.267, p = 0.016) and AI credibility (β_std = 0.196, p = 0.043) were the only significant predictors, whereas AI quality, cognitive absorption, and satisfaction showed positive but non-significant effects. These findings imply that AI-supported learning interventions should prioritize credible, trustworthy AI outputs and pedagogical designs that promote positive emotional experiences (e.g., comfort, reduced stress, motivation) to strengthen perceived critical-thinking benefits; overall, affective and trust-related factors appear to be central drivers of students’ positive AI perceptions, warranting validation in larger and longitudinal studies
Analisis Deskriptif Aspek Computational Thinking Mahasiswa dalam Penguatan Literasi Komputer Firdaus; Akbar Fadila; Fitra Yusuf; Nurrahmah Agusnaya
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

Perkembangan teknologi digital menuntut adanya keterampilan berpikir tingkat tinggi yang mampu mendukung literasi komputer dan problem solving di berbagai bidang. Salah satu keterampilan yang menjadi perhatian global adalah Computational Thinking (CT), yang meliputi abstraksi, dekomposisi, algoritmik thinking, evaluasi, dan generalisasi. Penelitian ini bertujuan untuk memetakan profil CT mahasiswa Indonesia melalui pendekatan kuantitatif berbasis kuesioner dengan 19 item pernyataan yang diisi oleh 46 responden dari berbagai perguruan tinggi. Analisis deskriptif dilakukan untuk mengidentifikasi kecenderungan responden pada setiap aspek CT. Hasil penelitian menunjukkan bahwa mahasiswa memiliki kecenderungan yang baik pada aspek algoritmik thinking, evaluasi, dan generalisasi, yang menandakan kemampuan berpikir prosedural, menilai solusi, serta mengadaptasi strategi ke permasalahan baru sudah cukup kuat. Sebaliknya, aspek dekomposisi masih berada pada tingkat sedang, menunjukkan perlunya penguatan keterampilan memecah masalah kompleks menjadi bagian yang lebih sederhana. Secara keseluruhan, profil ini menggambarkan bahwa CT mahasiswa telah berkembang dengan baik, namun masih memerlukan strategi pembelajaran yang lebih terarah untuk menyeimbangkan penguasaan di semua aspek. Temuan ini diharapkan dapat menjadi dasar pengembangan kurikulum dan model pembelajaran berbasis CT di pendidikan tinggi Indonesia.
ChatGPT Menantang Metodologi Pembelajaran Campuran dalam Pendidikan Teknik: Studi Kasus dalam Matematika Muh Amirul Mukmi; Muh Andhka Maharsaka Suaib; Andi Muhammad Faruq; Nurrahmah Agusnaya
Journal of Educational Studies in Science, Technology, Engineering, Arts and Humanities Vol.1 No.1 (2025): September 2025
Publisher : PT. Global Research Collaboration

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

Abstract

Penelitian ini mengusulkan penerapan ChatGPT sebagai instrumen inovatif dalam konteks pembelajaran matematika di pendidikan teknik. Dengan fokus pada metode pembelajaran campuran, kami menginvestigasi bagaimana integrasi teknologi model bahasa yang canggih seperti ChatGPT dapat memperkaya pengalaman belajar siswa. Studi kasus dilakukan untuk mengevaluasi dampak penerapan ChatGPT terhadap pemahaman materi matematika dan keterlibatan siswa. Hasil eksperimen menunjukkan bahwa penggunaan ChatGPT secara signifikan meningkatkan keterlibatan siswa dan memfasilitasi pemahaman konsep matematika yang kompleks. Temuan ini mendukung argumen untuk mengintegrasikan kecerdasan buatan dalam konteks pendidikan teknik, menantang paradigma tradisional pembelajaran campuran, dan membuka jalan untuk pengembangan lebih lanjut dalam meningkatkan efektivitas pembelajaran teknis menggunakan teknologi mutakhir.
Integrating Technology with Academic Success by Evaluating ChatGPT’s Quality Compatibility and Impact on Student Performance Irwansyah Suwahyu; Yohana Rara; Nur Syafitra Ramadhani; Rosidah; Putri Nirmala; Nurrahmah Agusnaya; Pramudya Asoka Syukur
Information Technology Education Journal Vol. 4, No. 2, May (2025)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v4i2.8532

Abstract

The use of artificial intelligence (AI) technology in higher education has become an important element to improve students' academic performance. ChatGPT, as one of the generative AI applications, offers speed, ease of use, and relevant responses to support students' learning activities. This study aims to analyze the relationship between overall technology quality, technology characteristics, technology task suitability, compatibility, and performance impact in using ChatGPT on students' academic performance. This study used a quantitative approach with a cross-sectional design and purposive sampling technique involving 182 active student respondents using ChatGPT. Data were collected through an online questionnaire using a 5-point Likert scale covering five main variables. The results of descriptive analysis show a mean value that illustrates that students generally have a positive perception of the use of ChatGPT in supporting their academic activities. These findings suggest that ChatGPT has great potential in improving student productivity and comprehension, although service quality, task suitability, and function compatibility need to be continuously improved to better suit academic needs. Thus, the implementation of ChatGPT in higher education needs to be planned adaptively and ethically in order to optimally support students' learning success in the digital era
Unraveling the Effects of AI Usage on Burnout among Programmers: An Apriori Algorithm Data Mining Approach Muhammad Fardan; Ana Sulistiana Alwi; Khalil Mubaraq Darwing; Dewi Fatmarani Surianto; Putri Nirmala; Nurrahmah Agusnaya
Information Technology Education Journal Vol. 4, No. 3, August (2025)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v4i3.9858

Abstract

Burnout is a growing problem across various industries, particularly among programmers who face high workloads and prolonged stress. In this digital era, the use of technologies such as AI can be a solution to reduce workloads and improve employee well-being. This study aims to identify how the use of AI can reduce burnout levels in programmers. The method used is a cross-sectional research design with data collection through a survey using the Google Form platform, and data analysis using descriptive techniques and the Apriori algorithm to find patterns in the relationship between the duration of AI use, workload, and burnout levels. The results show that the use of AI can help reduce burnout levels by lowering workloads, providing a basis for more effective interventions in the workplace.
A PLS-SEM Analysis of Basic Psychological Needs on Self-Regulation in Digital Learning: Insights from Self-Determination Theory Ahmad Faris Al Faruq; Muhammad Fardan; Andi Dio Nurul Awalia; Nurrahmah Agusnaya; M.Miftach Fakhri
Information Technology Education Journal Vol. 4, No. 4, November (2025)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v4i4.10813

Abstract

In the rapidly evolving digital age, technology-based learning has become integral to modern education, offering flexibility and accessibility while introducing challenges in student engagement and motivation. This study explores the relationship between basic psychological needs: autonomy, competence, and relatedness. Outlined in Self-Determination Theory (SDT) and self-regulated learning in digital environments. Utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM), data was collected from 737 students to examine how these needs impact self-regulation in digital learning. The findings reveal that fulfilling these psychological needs significantly enhances students' self-regulation, leading to improved learning outcomes. Autonomy, particularly when supported by digital tools, and competence, bolstered by immediate feedback and digital literacy, are crucial for fostering effective self-regulation. Relatedness, although less influential, remains important in maintaining motivation through social connections in online learning. The study contributes to the growing body of literature on SDT by highlighting the importance of creating digital learning environments that cater to students' psychological needs, thereby enhancing motivation and academic success.
Co-Authors Abil Alam Ahmad Faris Al Faruq Akbar Fadila Ana Sulistiana Alwi Andi Anggi Kemalasari Andi Dio Nurul Awalia Andi Muhammad Faruq Arum Putri Rahayu Dewi Fatmarani Surianto Fadhil Zil Ikram Fajriani Azis Firdaus Fitra Yusuf Irwansyah Suwahyu Khalil Mubaraq Darwing M. Andika Aswa M. Miftach Fakhri M.Miftach Fakhri Muh Amirul Mukmi Muh Andhka Maharsaka Suaib Muh. Yusril Anam Muhammad Fardan Muhammad Husair Nawawi Nur Syafitra Ramadhani Nur Wahyu Adrian Nurwahyuni Paallo Pramudya Asoka Syukur Putri Nirmala Rachmawaty Kadir Rahmawati Rina Asriani J Tudon B Rosidah Rosidah Saipul Abbas Sakinah Mawaddah Santi Widyawati Ummul Khaeri Masna Yohana Rara