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IJIE (Indonesian Journal of Informatics Education)
Published by Universitas Sebelas Maret
ISSN : -     EISSN : 25490389     DOI : -
Core Subject : Science, Education, Engineering,
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering
IJIE (Indonesian Journal of Informatics Education) is is a scientific journal promoting the study of, and interest in, informatics education. The journal publishes empirical papers on information systems, informatics, the use of technology learning, and distance learning. It is an international journal published by the Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret, Indonesia bi-annually on June and December (ISSN: 2549-0389 (Online))
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Articles 7 Documents
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Search results for , issue "Vol 8, No 2 (2024)" : 7 Documents clear
Sentiment Analysis of Netizens on Constitutional Court Rulings in the 2024 Presidential Election Wahyudi Ariannor; Sami M A B Alshalwi; Budi Susarianto
IJIE (Indonesian Journal of Informatics Education) Vol 8, No 2 (2024)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijie.v8i2.94614

Abstract

AbstractOnline conversations among netizens play an important role in forming collective opinions and views about important events, including judicial decisions such as those taken by the Constitutional Court (MK). This research explores sentiment analysis of the Constitutional Court’s decisions, especially in the context of the presidential election, using the Support Vector Machine (SVM), Logistic Regression, and Naive Bayes algorithms. Previous studies on public sentiment toward the Constitutional Court’s decision provide a basis. Still, this research focuses on a different context, analysing sentiment toward the Constitutional Court’s decision in the 2024 presidential election dispute. This study adopts an experimental methodology, involving several key stages such as data collection through Twitter web scraping, labelling, pre-processing, TF-IDF weighting, and algorithm testing. Evaluation using a confusion matrix shows comparable accuracy among SVM, Logistic Regression, and Naive Bayes, with SVM and Logistic Regression demonstrating superior precision and F1 scores. Negative sentiment carries greater weight than neutral and positive sentiment, highlighting potential social tensions and the need for effective communication and deeper analysis to understand the root causes of negativity. The SVM and logistic regression algorithms have proven effective in understanding public sentiment towards the Constitutional Court’s decisions in a political context, providing valuable insights for understanding the dynamics of public opinion.
The Application of Arduino-Based Line Follower Robotics Technology as a Tool to Enhance Students' Self-Efficacy Slamet Kurniawan Fahrurozi; Muhammad Hassan Massaty; Cucuk Wawan Budiyanto; Bayu Sutanto
IJIE (Indonesian Journal of Informatics Education) Vol 8, No 2 (2024)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijie.v8i2.97994

Abstract

This study focuses on a detailed analysis of the Robotics Self-Efficacy Test, aiming to evaluate its effectiveness in measuring students' confidence levels across specific robotics tasks. Using robotics as a learning medium, this research enhances student engagement and practical skills in technical areas. Addressing a gap in precise self-efficacy measurement tools for robotics education, the study employs the RSE-Test to assess confidence in essential robotics tasks, such as robot assembly, programming, and control. Data collection involved a 10-item RSE-Test questionnaire completed by 30 students engaged in robotics activities, followed by a statistical analysis to calculate mean scores, standard deviations, item-total correlations, and Pearson correlational analysis. The overall mean score was 3.9835, indicating high confidence, with a pooled standard deviation of 0.687, showing minimal variation. The pooled Standard Error of the Mean was 0.128, reflecting high precision in estimating the overall mean. Cronbach’s Alpha of 0.810 confirms the test's strong internal consistency, and item-total correlations ranged from 0.423 to 0.703, supporting the reliability of the RSE-Test. Pearson correlation analysis revealed significant relationships between items, further validating the tool. Results indicate high self-efficacy in basic robotics tasks, although students showed slightly lower confidence in more advanced tasks, suggesting areas for further support. This study validates the RSE-Test as an effective tool for measuring self-efficacy in technical education, emphasizing the role of foundational skills in building student confidence. The findings provide valuable insights for curriculum developers, suggesting the need for targeted support in advanced robotics tasks.
[Retracted Article] Mapping Research Trends of TikTok in Education: A Bibliometric Analysis Siti Nurjanah; Shaufi Ramadhani; Zafrullah Zafrullah; D’aquinaldo Stefanus Fani Seran; Rooskartiko Bagas Rahoetomo; Sandry Rory
IJIE (Indonesian Journal of Informatics Education) Vol 8, No 2 (2024)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijie.v8i2.83732

Abstract

NOTICE OF ARTICLE RETRACTION Dear Readers and Stakeholders,We hereby announce that the article titled "Mapping Research Trends of TikTok in Education: A Bibliometric Analysis", published in IJIE (Indonesian Journal of Informatics Education), Volume 8, Issue 2 (December 2024), has been officially retracted from publication.Reason for Retraction:Following a thorough internal investigation, it was discovered that a violation of publication ethics was committed by the corresponding author. Specifically, the violation involved the addition of author names by editing the article metadata after the article had been accepted for publication. This act is deemed an exploitation of the publishing system by including authors whose contributions could not be clearly verified in the preparation of the article.This behaviour violates the principles of transparency, academic integrity, and the ethical publishing guidelines established by IJIE (Indonesian Journal of Informatics Education), as well as the standards set forth by the Committee on Publication Ethics (COPE).Further Actions:The article has been officially retracted and will be clearly marked as such on our publication platform.Information regarding this retraction will remain accessible to ensure transparency and accountability within the academic community.Further steps will be taken in accordance with our publication ethics policies.We reaffirm our commitment to upholding the highest standards of academic integrity and quality in scientific publishing. We sincerely apologise to our readers, contributing authors, and the wider scholarly community for any inconvenience caused by this matter.Thank you for your understanding and continued support. Yours sincerely,Editor-in-ChiefAbstract:This study aims to identify research trends related to the use of TikTok in the field of education using bibliometric analysis. Data was obtained from 46 publications obtained from the Scopus database in 2020–2023, which were filtered based on TikTok keywords in the context of education. Data analysis was carried out with the biblioshiny package of the RStudio application. The results showed that publications increased sharply in 2022. Geographically, China and the United States contributed the most. The main keywords included "social networking", "TikTok", and "students" representing the research trends on utilising TikTok for learning. The most cited articles indicate TikTok's potential as an innovative pedagogical tool to increase learners’ engagement and motivation and expand public access to education and health information. Further research was recommended to enrich multidisciplinary perspectives and maximise the benefits of TikTok for learning.
Access to, Use, and Effect of Open Educational Resources: The Perspectives of LIS Academics in Selected Nigerian Universities Adeyinka TELLA; Olufemi Peter Owoeye; Aderinola Ololade Dunmade
IJIE (Indonesian Journal of Informatics Education) Vol 8, No 2 (2024)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijie.v8i2.85288

Abstract

This study investigated access to, use of, and the effect of Open Educational Resources (OER) on LIS academics in Nigeria. The study adopted a purely quantitative method, using a survey as the research design. The population of the study comprised LIS academic staff in Nigerian universities. Through a total enumeration method, a sample of 140 LIS academics from 15 universities in Nigeria was selected. A questionnaire developed for data collection was administered to the 140 respondents, of which 133 copies were returned. Seven objectives were developed to guide the study. The results demonstrated that office documents such as Word and PowerPoint, open textbooks, lecture notes, quizzes and tutorials, MOOCs, learning modules, and open courseware are the OER resources most frequently accessed by LIS academics. Mobile phones and laptop computers are the primary devices used by LIS academics for accessing OER. OER are used by LIS academics for teaching and learning, research, preparation for workshops, seminars, conference presentations, and class notes. The effects of OER on LIS academics include the ability to use materials created by other colleagues and customise course materials to create an ideal course packet or textbook. Policies guiding the use of OER include equal access, protection of intellectual property rights, and open licences such as Creative Commons. The challenges LIS academics encounter when using OER include frequent power outages, untimely updates of OER repositories, and prolonged periods spent searching for resources in institutional repositories.
GenAI and effective reading among university students: Prospects, challenges, and future directions George Matto; Jaffar Msafiri Ponera; Valeria Kyumana
IJIE (Indonesian Journal of Informatics Education) Vol 8, No 2 (2024)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijie.v8i2.97595

Abstract

Continuous advancements in the fields of science and technology have led to the emergence of innovative technologies such as Generative Artificial Intelligence (GenAI). While there have been increased use of GenAI among university students, some scholars relate its use with negative impacts regarding students reading habits while others relate it with positive. It is against this backdrop that the present study was carried out to explore prospects, challenges and future directions of GenAI in the developing effective reading amongst university students. The study employed systematic review of literature. Findings revealed that GenAI presents both prospects and limitations for students’ effective reading. improved accessibility, convenience of reading, personalized reading resources and interactive reading were found to be the potential prospects. Regarding limitations, the study found that GenAI can potentially create students’ overdependency on it. In addition, there are potential biasness and inaccuracies of AI algorithms that can lead to a generation of biased reading contents. The system can also lead to breach of data privacy and it is resources intensive.  Most of the limitations are, however, manageable. Thus, it was reasonably concluded that the prospects outweigh the limitations. It was, further, found that future directions of AI in developing reading environments involve integration of AI with virtual reality, diminished human-human interaction, human-AI integration, and lifelong learning. The study calls for universities to institute and operationalize students’ data governance and protection policies, among other recommendations.
Digital Empowerment in Social Work: Leveraging AI to Enhance Educational Access in Developing Nations Zvinodashe Revesai; Benjamin Tungwa; Telson Anesu Chisosa; Vanessa Runyararo Meki
IJIE (Indonesian Journal of Informatics Education) Vol 8, No 2 (2024)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijie.v8i2.92951

Abstract

Social work education in developing countries faces significant challenges, including limited resources, restricted access to current knowledge, and inadequate training opportunities. This study aims to examine the potential of emerging Artificial Intelligence (AI) technologies in empowering social work students by enhancing access to information through machine translation and intelligent search tools, improving resource availability via virtual simulations and adaptive learning platforms, and integrating AI-powered self-help tools into the curriculum. A qualitative research design was employed, utilizing in-depth interviews with 16 educators and 8 field training officers, along with focus group discussions involving 24 social work students across selected institutions in Zimbabwe. All interviews were audio-recorded with participant consent, with translators assisting where necessary for local languages. Additional data were collected from documents, public reports, learning platforms, and policy papers to provide context on AI adoption strategies. Data were analyzed using thematic analysis, examining cases and models where AI has expanded access to scholarly materials through automated translation services, enabled localized resources through virtual training simulations, and facilitated the incorporation of culturally aligned self-help tools such as AI chatbots and wellness applications. The findings show that, with careful implementation and consideration of the context, artificial intelligence can reduce inequalities in education and enhance students' abilities through personalized learning paths, virtual environments for practice, and automated feedback systems. However, this research points out the need for addressing the digital divide and ethical issues associated with artificial intelligence, including problems of privacy and algorithmic bias. The study concludes by making a call for further research into models of safe and equitable AI integration in social work education.
The Dark Side of Social Media: Analysing Dark Pattern Combinations and Their Impacts Hansika Ukgoda
IJIE (Indonesian Journal of Informatics Education) Vol 8, No 2 (2024)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijie.v8i2.91666

Abstract

In today’s digital era, technology is essential in daily life, transforming interactions and activities. However, the rise of “Dark Patterns - deceptive design practices in websites and apps raises significant ethical concerns. Originally defined by User Experience Designer Harry Bringull, dark patterns manipulate users into actions like involuntary purchases and subscriptions. This study explored dark patterns on social media networking sites (SNSs), focusing on two key questions: Do platforms use specific dark patterns in combination, and how do these combinations impact user interaction and experience?Utilizing cognitive walkthroughs with UI/UX experts, this research examined dark patterns on YouTube, LinkedIn, Telegram, and WhatsApp. Researchers conducted platform-specific evaluations to examine and understand the various combinations of manipulative design elements. The findings revealed prevalent combinations of dark patterns and evaluated their effect, addressing a critical gap concerning social media's ethical implications in the Human-Computer Interaction (HCI) field. The findings contribute to disclosing ethical design practices and promoting a more user-friendly approach to UI design that enhances user well-being and trust in digital environments.

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