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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) Jurnal Performa: Jurnal Manajemen dan Start-up Bisnis IJIIS: International Journal of Informatics and Information Systems International Journal for Applied Information Management Journal of Current Research in Blockchain
Izumi, Calvina
Unknown Affiliation
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Social Sciences

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Misconceptions of metaverse: from etymology to technology Putawa, Rilliandi Arindra; Izumi, Calvina; Sugianto, Dwi; Ghaffar, Soeltan Abdul
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 13, No 2: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v13i2.pp314-320

Abstract

The emergence of the metaverse in society is followed by certain confusions, whereas the line between virtual reality and the metaverse remains unclear. Ironically, this has affected the development of the metaverse itself, focusing more on virtual reality while being one of its side components. This has led to the concept losing popularity compared to artificial intelligence technology. This research is a qualitative study that aims to explore the issues at the root of misconceptions and reconstruct the true meaning of the metaverse itself. This research indicates that the misconception already existed when the term was first used alongside virtual reality technology. The term "meta" refers to a higher reality, whereas the terms "digiverse" or "virtuverse" can be used, considering that the terms "digital" and "virtual" can refer to realities lower than the universe.
Uncovering the Efficiency of Phishing Detection: An In-depth Comparative Examination of Classification Algorithms Sugianto, Dwi; Putawa, Rilliandi Arindra; Izumi, Calvina; Ghaffar, Soeltan Abdul
International Journal for Applied Information Management Vol. 4 No. 1 (2024): Regular Issue: April 2024
Publisher : Bright Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijaim.v4i1.72

Abstract

This research aims to investigate the potential security risks associated with phishing email attacks and compare the performance of three main classification algorithms: random forest, SVM, and a combination of k-fold cross-validation with the xgboost model. The dataset consists of 18,634 emails, with 7,312 identified as phishing emails and 11,322 considered safe. Through experiments, the combination of k-fold cross-validation and xgboost demonstrated the best performance with the highest accuracy of 0.9712828770799785. The email classification graph provides a visual insight into the distribution of classification results, aiding in understanding patterns and trends in phishing attack detection. The analysis of the ROC curve results indicates that k-fold cross-validation and xgboost have a higher AUC compared to random forest and SVM, signifying a better ability to predict the correct class. The conclusion emphasizes the importance of the combination of k-fold cross-validation and xgboost in enhancing email security, with the potential for increased accuracy through parameter adjustments.
Pengaruh Workplace Ostracism, Workplace Loneliness melalui Cyberloafing terhadap Employees’ Performance pada Digital Agency Izumi, Calvina
PERFORMA Vol. 8 No. 4 (2023): Performa
Publisher : Universitas Ciputra Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37715/jp.v8i4.3981

Abstract

Peran internet dalam industri digital marketing agency dapat membawa dampak positif dan negatif. Persaingan digital yang makin ketat terus mendorong digital agency untuk menciptakan ide kreatif dan inovasi menarik agar dapat bersaing. Dalam tingginya tekanan, tanpa disadari internet menjadi celah yang digunakan semena-mena oleh karyawan perusahaan, cyberloafing. Penelitian ini dilakukan untuk menguji pengaruh Workplace Ostracism, Workplace Loneliness terhadap Employees’ Performance melalui Cyberloafing pada startup Digital Agency. Responden penelitian ini berasal dari seluruh populasi PT XXX yang merupakan startup yang menerapkan sistem kerja hybrid dan dominan menggunakan internet. Variabel yang digunakan pada penelitian ini yaitu Workplace Ostracism, Workplace Loneliness sebagai variabel independen, Employees’ Performance variabel dependen, dan Cyberloafing sebagai variabel mediasi. Metode yang digunakan dalam penelitian ini yaitu metode analisis berupa Partial Least Square (PLS) dengan software SmartPLS. Metode pengambilan sample dilakukan dengan sampling jenuh melalui pembagian kuesioner kepada 53 karyawan PT XXX. Berdasarkan analisis yang dilakukan, diperoleh hasil bahwa Workplace Ostracism, Workplace Loneliness, dan Cyberloafing berpengaruh signifikan terhadap Employees’ Performance, Cyberloafing tidak dapat mendukung mediasi pengaruh baik Workplace Ostracism dan Workplace Loneliness terhadap Employees’ Performance pada karyawan PT XXX.
A Quantitative Analysis of Artificial Intelligence’s Impact on Students’ Mindset and Critical Thinking in Higher Education Prambudi, Niko Lugas; Putawa, Rilliandi Arindra; Izumi, Calvina
International Journal of Informatics and Information Systems Vol 7, No 4: December 2024
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v7i4.222

Abstract

The rapid advancement of Artificial Intelligence (AI) has significantly transformed higher education, redefining how students learn, reason, and engage with academic content. This study investigates the impact of AI utilization on students’ mindsets and critical thinking skills within university learning settings. Employing a quantitative research design, data were gathered through an online questionnaire administered to 28 students from various academic disciplines. The survey assessed students’ engagement with AI tools including ChatGPT, Gemini, and Perplexity in learning processes such as understanding course materials, completing assignments, and problem-solving activities. The results indicate that most participants perceive AI as highly beneficial for enhancing comprehension, efficiency, and creativity in academic work. Students report that AI applications help them approach problems from diverse perspectives and stimulate idea generation. Nevertheless, concerns about overdependence are evident, as 53.6% of respondents believe that excessive reliance on AI may diminish autonomy and critical reasoning capacity. While a majority of students claim to verify AI-generated responses, a minority remain unaware of biases and inaccuracies, emphasizing the need to strengthen AI literacy in academic contexts. Overall, the findings suggest that AI serves as both a catalyst for deeper learning and a potential risk to intellectual independence. Its integration into higher education must therefore be approached with pedagogical mindfulness, ensuring that AI acts not as a replacement for human thought but as a tool for reflection, creativity, and metacognitive growth. Educators are encouraged to design learning experiences that require students to analyze, compare, and critique AI outputs critically. In conclusion, AI represents a dual-edged innovation: when applied ethically and reflectively, it can foster a growth-oriented mindset and strengthen critical thinking, but without proper guidance, it may cultivate intellectual complacency and dependency.
Analyzing Price Volatility of Hedera Hashgraph Using GARCH Models: A Data Mining Approach Izumi, Calvina; Setiawan, Wilbert Clarence; Ghaffar, Soeltan Abdul
Journal of Current Research in Blockchain Vol. 2 No. 2 (2025): Regular Issue June 2025
Publisher : Bright Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jcrb.v2i2.35

Abstract

This study employs the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model to analyze the volatility dynamics of Hedera Hashgraph, a prominent cryptocurrency. Using a dataset of 1,901 daily price observations, we investigate the presence of volatility clustering and the persistence of market shocks, which are hallmarks of financial markets. The GARCH(1,1) model demonstrates robust performance, with a Log-Likelihood of 2927.50, AIC of -5846.99, and BIC of -5824.79, confirming its suitability for volatility estimation. Key findings reveal significant volatility clustering, with alpha (α = 0.20) and beta (β = 0.78) indicating moderate sensitivity to recent shocks and high persistence of volatility, respectively. Visualizations of conditional volatility and historical price data highlight the inverse relationship between price stability and volatility, with high volatility periods accounting for 33% of the dataset. These insights underscore the importance of real-time volatility monitoring for risk management and investment strategies. The study concludes by suggesting future research directions, including the integration of GARCH models with machine learning techniques and the exploration of external factors influencing cryptocurrency price dynamics.
Co-Authors Ghaffar, Soeltan Abdul Prambudi, Niko Lugas Putawa, Rilliandi Arindra Setiawan, Wilbert Clarence Sugianto, Dwi