Article Per Year (5 Year)
p-Index From 2021 - 2026
2.405
P-Index
This Author published in this journals
All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Proceedings of KNASTIK TELKOMNIKA (Telecommunication Computing Electronics and Control) PROSIDING CSGTEIS 2013 International Conference on Engineering and Technology Development (ICETD) Seminar Nasional Informatika (SEMNASIF) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Seminar Nasional Teknologi Informasi Komunikasi dan Industri Prosiding Seminar Nasional Teknoka Journal Information System Development Jurnal ULTIMA InfoSys Jurnal Teknologi Informasi dan Pendidikan Journal of Applied Data Sciences Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) IICS Jurnal Sains Teknologi dan Sistem Informasi Proceeding National Conference Business, Management, and Accounting (NCBMA) GIAT: Teknologi untuk Masyarakat
Arnold Aribowo
Universitas Pelita Harapan
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics Social Sciences Other

Published : 35 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : journal of applied data sciences

 1 
Unsupervised Learning for MNIST with Exploratory Data Analysis for Digit Recognition Hery, Hery; Haryani, Calandra A.; Widjaja, Andree E.; Tarigan, Riswan E.; Aribowo, Arnold
Journal of Applied Data Sciences Vol 5, No 2: MAY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i2.184

Abstract

This research investigates the application of unsupervised learning techniques for digit recognition using the MNIST dataset. Through a comparative analysis, various dimensionality reduction methods, including ISOmap, PCA, and tSNE, were evaluated for their effectiveness in visualizing and processing the MNIST data. The findings reveal that tSNE consistently outperforms ISOmap and PCA in terms of accuracy, F1- score, precision, and recall, showcasing its superior capability in preserving relevant information within the dataset. Utilizing tSNE for visualizing and clustering digits provides valuable insights into the underlying structure of the dataset, uncovering complex patterns in digit relationships. These results contribute to the advancement of digit recognition systems, offering potential improvements in classification accuracy and model reliability. The success of tSNE highlights the importance of nonlinear dimensionality reduction techniques in handling complex datasets, such as MNIST. This research underscores the significance of unsupervised learning approaches, particularly tSNE, in enhancing digit recognition systems' performance, with implications extending across various application domains. Continued research is recommended to explore further applications and potentials of unsupervised learning techniques and to deepen our understanding of the MNIST dataset's structure and complexity.
Cognitive and Technological Factors Shaping Students’ Sustained Use of ChatGPT in Higher Education Aribowo, Arnold; Hery, Hery; Widjaja, Andree Emmanuel
Journal of Applied Data Sciences Vol 7, No 2: May 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i2.1291

Abstract

This study examines the cognitive and technological factors shaping students' sustained use of ChatGPT in Indonesian higher education. Despite the rapid adoption of generative Artificial Intelligence (AI) in education, a clear understanding of the factors sustaining continued engagement with such systems remains limited. While continuance intention has been widely examined, the application of the Expectation–Confirmation Model (ECM) in generative AI contexts remains underexplored. This gap is especially evident when considering the role of AI-specific system attributes in shaping post-adoption evaluations. Although ECM has been extended with various constructs in prior studies, the specific integration of AI characteristics, particularly perceived intelligence and anthropomorphism, has not been explored in generative AI use in education, especially within Indonesian higher education. To address this gap, a multi-theoretic framework integrating ECM and AI characteristics was developed. Data from 322 Indonesian students were analyzed using Partial Least Squares-Structural Equation Modeling. All ten hypotheses were supported, and the model explains 43.3% of the variance in continuance intention (R² = 0.433). Perceived Intelligence strongly influences Perceived Anthropomorphism with a path coefficient of 0.591, representing the strongest relationship in the model, while other paths demonstrate moderate or modest effects. The findings confirm ECM's robustness in generative AI settings and highlight the pivotal role of AI characteristics in shaping post-adoption evaluations and sustained use. These results contribute to the growing body of research on generative AI adoption in education by demonstrating how system intelligence and human-like interaction jointly influence continuance intention. The findings also offer practical guidance for AI developers to enhance system intelligence and natural interaction. Future research could explore how students experience AI over time and what shapes their sustained use using different research methods.
Co-Authors Alencia Haryani, Calandra Alvent Ciayadi Anton Yunus Timothy Adichandra Bobby Pranata Budi Berlinton Sitorus Christian Marsel Wijaya2 Debora Kathrin Yuwono Debora Kathrin Yuwono Deo Kiatama Dina Stefani Gennady, Erick Greisye Magdalena Hadinata Hadinata Handy Handy Haryani, Calandra A. Haryani, Calandra Alencia Hendra Tjahyadi Heny Ispur Pratiwi Heny Ispur Pratiwi Hery Hery Hery Hery I Made Murwantara Irene A. Lazarusli Jennifer Novia Nursalim Jocelyn Olivia Julian Fetriandhy Altanijah Kevin Arie Sandy Kie Van Ivanky Saputra Kristian Frits Harris Kusno Prasetya Martin Gunawan Michelle Angelica Mitra, Aditya R. Prasetya, Kusno Putra, Alfa Satya S.M. Nababan S.M. Nababan Samuel Lukas Sepreni Sepreni Suryasari Suryasari Tania Jovita Wibowo Tarigan, Riswan E. Tiffani Maria Bernadetta Widjaja, Andree E. Yogih Suharta Tjia Yuda Desela Yugopuspito, Pujianto Yunita Thedykurnia