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All Journal JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Ilmiah Dinamika Sosial Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika
Sudestra, I Made Ardi
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Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Library & Information Science Social Sciences

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IMPROVING DIGITAL LEARNING: EVALUATING THE U LEARN LMS WITH THE SYSTEM USABILITY SCALE Sudestra, I Made Ardi; Agustini, Ni Wayan Eva; Gunawan, I Made Agus Oka; Indrawan, Gede; Hakimi, Musawer
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 4 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i4.6910

Abstract

The assessment of the usability of online learning systems is becoming more and more critical in order to ensure that users have the best possible experience. This study employed the System Usability Scale (SUS) to assess the usability of the learning management system at UNDIKNAS, using 68 students from various academic programs as participants. The employed methodology is administering a SUS questionnaire consisting of 10 items on a Likert scale from 1 to 5. The points are computed using the standard SUS methodology and multiplied by 2.5 to derive the final score. The analysis disclosed an average SUS score of 56.65, falling short of the academic usability benchmark 68. The score distribution visualization indicated that most respondents rated between 50 and 60, highlighting the need for system improvement. The SUS assessment of the learning management system at UNDIKNAS reveals that the system's usability necessitates improvement. Key recommendations include improving the user interface, optimizing navigation, and providing user guides to enhance the overall user experience
THE INFLUENCE OF EMERGING TECHNOLOGIES ON COMMUNICATION PRACTICES IN THE DIGITAL AGE Hakimi, Musawer; Kohistani, Ahmad Jamy; Azimy, Abdul Shakoor; Sudestra, I Made Ardi
Jurnal Ilmiah Dinamika Sosial Vol 9 No 1 (2025)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/jids.v9i1.6500

Abstract

The speed with which emerging digital technologies have changed our communications has impacted many aspects of the communication process wherever people interact in their personal and professional lives. In part this study sought to explore the influence of emerging digital communication technologies on users’ communication behaviors, perceptions and attitudes. A quantitative research design was used. Data was collected online through an online survey. We collected data from 278 participants age 18 years and older. Stratified random sampling was used to provide an adequate demographic representation. The instrument consisted of demographic items, technology use patterns and Likert-style questions to depict users’ perception of if their communication changed and about their attitude toward technology.  Descriptive statistics indicated very high use rates of e-mail (89.3%), AI (86.5%) and video conferencing (84.0%). While technology use varied daily, 27.3% of participants indicated they spent more than five hours each day communicating digitally. When user perceptions associated with technology impacts were reported as moderate agreements that the emerging technologies improved the speed and access of communication; however, concussions about the quality of the interaction that replaced face-to-face time was are something to think about. We'd like to point out that the overall reliability of the survey instrument was reasonable69 for a couple of key sections, Cronbach's alpha was above 0.7. The initial findings of this research indicate that while emerging digital technologies have improved the speed of connection and efficiency in communication, users are still careful of the social ramifications. Future discussions and strategies should look to balance technological gains and the need for some form of inter-personal relationship. This research is a contribution to the literature for research and practice, especially as it relates to the burgeoning evolution of digital communications.
SPAM EMAIL CLASSIFICATION USING SUPPORT VECTOR MACHINE (SVM) AND TF-IDF: A CASE STUDY WITH THE TREC 2007 AND ENRON-SPAM DATASETS Paramartha, I Gusti Ngurah Darma; Sudestra, I Made Ardi; Gama, Adie Wahyudi Oktavia; Prathama, Gede Humaswara
Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 19 No. 2 (2025): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47111/jti.v19i2.22770

Abstract

Spam emails represent a substantial concern within the digital landscape, impeding users with unsolicited communications. This study elucidates the utilization of a Support Vector Machine (SVM) coupled with a TF-IDF Vectorizer for categorizing emails into spam and non-spam classifications. The model was developed utilizing two publicly accessible pre-processed datasets: the TREC 2007 Public Spam Corpus and the Enron-Spam Dataset. By employing the TF-IDF algorithm, which allocates heightened importance to infrequent yet pertinent terms, alongside SVM, renowned for its efficacy in textual classification, the model exhibits remarkable efficacy, achieving an accuracy of 99.04%, a precision of 98.57% and a recall of 99.62%. These findings underscore the model's formidable capacity to discern spam emails while concurrently minimizing false positives accurately. This is critical for real-world applications where authentic emails must not be erroneously categorized as spam. Furthermore, this study elaborates on the justification for the selection of TF-IDF and SVM in the context of spam email classification, in addition to the evaluation outcomes of the model, which align with existing literature, wherein the integration of SVM with TF-IDF has demonstrated substantial performance in spam detection endeavours.
Co-Authors Adie Wahyudi Oktavia Gama Agustini, Ni Wayan Eva Azimy, Abdul Shakoor Gede Humaswara Prathama Gede Indrawan Hakimi, Musawer I Gusti Ngurah Darma Paramartha I Made Agus Oka Gunawan Kohistani, Ahmad Jamy