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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 Educational Studies in Science, Technology, Engineering, Arts and Humanities
Putri Nirmala
Universitas Negeri Makassar
Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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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.
Persepsi Mahasiswa terhadap Infrastruktur Pendidikan dan Integrasi Computational Thinking di Perguruan Tinggi M. Nurul Fajri; Ruslan Kadir; Putri Nirmala; Rachmawaty Kadir; Rahmawati
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: 10.61220/21tmsg76

Abstract

The disparity in educational infrastructure across universities in Indonesia presents a significant barrier to the integration of computational thinking (CT) in higher education. This study aims to explore students’ perceptions of educational infrastructure development and the integration of CT in university learning. A descriptive quantitative method was employed using a Likert-scale questionnaire distributed to 73 university students. The results show that students perceive CT as highly relevant for enhancing critical thinking and problem-solving skills, with strong support for its integration into curricula. However, perceptions regarding the adequacy of educational infrastructure in Indonesia remain neutral to negative. Students also highlighted the importance of teacher and parent roles, as well as equitable access to professional training for successful CT implementation. These findings suggest that while awareness of CT’s relevance is high, systemic improvements in infrastructure and educator capacity are essential to support effective implementation in higher education.
ChatGPT dalam Dunia Virtual: Eksplorasi Pemanfaatan AI dalam Lingkungan Pembelajaran Mahasiswa Mutmainnah; Nurul Azizah; Putri Nirmala; Hajar Dewantara; Andika Isma
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/ev7sxe85

Abstract

The rapid development of information and communication technology presents challenges in higher education, particularly regarding students’ limited understanding of how to effectively integrate emerging tools like ChatGPT and Metaverse into learning. This study aims to explore students’ perceptions of ChatGPT utilization within the Metaverse learning environment at Universitas Negeri Makassar. A mixed-method approach was applied by distributing online questionnaires to 60 students across various cohorts and conducting interviews with selected respondents. The findings reveal that most students perceive ChatGPT positively, with 56% rating it effective in supporting learning, 58% expressing comfort in using it for academic tasks, and over 70% acknowledging its role in enhancing learning efficiency, critical thinking, and confidence in discussions. Moreover, ChatGPT was reported to improve access to learning resources, problem-solving in academic tasks, and overall learning quality, despite some students facing minor challenges in adoption. These results suggest that ChatGPT, when integrated into Metaverse-based learning, has significant potential to enhance educational outcomes, provided institutions offer proper guidance and support to maximize its benefits.
Explaining AI Anxiety Among University Students: The Roles of Career Anxiety, Dehumanization, and Algorithmic Fairness Mustamin; Ahmad Syarif Hidayatullah; Putri Nirmala; Akhmad Affandi; Della Fadhilatunisa
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.v1i2.10

Abstract

Beyond its instructional benefits, AI in higher education can evoke anxiety when students perceive AI as diminishing human uniqueness, disrupting career trajectories, or operating in ways that feel difficult to evaluate or contest. This study aims to examine the effects of career anxiety, dehumanization, and perceived algorithmic fairness on students’ AI anxiety in the context of AI-supported learning. Using an explanatory quantitative survey design, data were collected from 70 university students who actively used AI-based learning tools, and the proposed relationships were tested using PLS-SEM. The results indicate that career anxiety positively predicts AI anxiety (β = 0.234, t = 1.691, p = 0.045) and dehumanization is the strongest predictor (β = 0.415, t = 2.958, p = 0.002), whereas perceived algorithmic fairness is not significant (β = 0.103, t = 0.740, p = 0.230), with the model explaining 48.2% of the variance in AI anxiety (R² = 0.482). These findings imply that AI anxiety is driven more by emotional and identity-related threats than by fairness evaluations, suggesting that institutions should adopt human-centered AI integration, strengthen AI literacy, and provide career-focused and psychological support to reduce student anxiety in AI-supported learning environments.
Analisis Penerimaan Masyarakat berbasis EXT TAM terhadap Aplikasi Kesehatan Digital untuk Konsultasi Jarak Jauh Rachmat Ramadhan; Muh. Syarif Hidayatullah; Dewelia Irien Pasa; Putri Nirmala
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 membahas implementasi layanan telemedicine di Pakistan, khususnya di daerah pedesaan, yang dihadapkan pada tantangan aksesibilitas terhadap layanan kesehatan. Dengan latar belakang kurangnya fasilitas kesehatan dasar di pedesaan dan tingginya angka kematian bayi dan ibu, layanan telemedicine menjadi solusi yang menjanjikan. Penelitian ini mencoba menganalisis faktor-faktor yang mempengaruhi kesediaan pasien untuk mengadopsi layanan telemedicine. Literatur terkait menunjukkan bahwa telemedicine dapat meningkatkan aksesibilitas fasilitas perawatan kesehatan, terutama di lingkungan pedesaan. Namun, resistensi pengguna masih menjadi hambatan utama yang perlu diatasi. Penelitian sebelumnya menyoroti peran faktor sosial dalam mengubah perilaku pengguna terhadap penerimaan teknologi baru. Penelitian ini mencoba menjawab pertanyaan-pertanyaan yang masih belum terjawab, seperti hambatan apa yang mempengaruhi niat pasien untuk menggunakan layanan telemedicine di negara berkembang seperti Pakistan dan sejauh mana masyarakat telah menerima dan memahami layanan tersebut. Penelitian ini dianggap penting untuk memahami resistensi pengguna dan mengelola faktor-faktor yang mempengaruhi penerimaan teknologi baru. Metodologi penelitian menggunakan model penerimaan layanan Telemedicine berdasarkan Technology Acceptance Model (TAM). Instrumen penelitian berupa kuesioner dengan skala Likert digunakan untuk mengumpulkan data dari pasien di rumah sakit dan perawatan rawat jalan. Analisis data menggunakan Partial Least Squares (PLS) untuk menguji dan memvalidasi model. Hasil dari penelitian ini diharapkan dapat memberikan wawasan baru dalam pengembangan literasi kecerdasan buatan, khususnya dalam konteks layanan telemedicine di Pakistan. Diharapkan juga dapat memberikan manfaat bagi pemerintah, pembuat kebijakan, dan penyedia layanan kesehatan dalam memahami faktor-faktor yang mempengaruhi kesuksesan implementasi layanan telemedicine di daerah pedesaan Pakistan.
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.
Co-Authors Ahmad Syarif Hidayatullah Akhmad Affandi Ana Sulistiana Alwi Andika Isma Della Fadhilatunisa Dewelia Irien Pasa Dewi Fatmarani Surianto Fadhil Zil Ikram Hajar Dewantara Irwansyah Suwahyu Khalil Mubaraq Darwing M. Miftach Fakhri M. Nurul Fajri Muh. Syarif Hidayatullah Muhammad Fardan Mustamin Mutmainnah Nur Syafitra Ramadhani Nurrahmah Agusnaya Nurul Azizah Pramudya Asoka Syukur Rachmat Ramadhan Rachmawaty Kadir Rahmawati Rosidah Rosidah Ruslan Kadir Yohana Rara