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INDONESIA
Journal of Information Systems and Informatics
Published by Asosiasi Doktor Sistem Informasi Indonesia
ISSN : 26565935     EISSN : 26564882     DOI : 10.63158/journalisi
Core Subject : Science,
Computer Science & IT
Journal-ISI is a scientific article journal that is the result of ideas, great and original thoughts about the latest research and technological developments covering the fields of information systems, information technology, informatics engineering, and computer science, and industrial engineering which is summarized in one publisher. Journal-ISI became one of the means for researchers to publish their great works published two times in one year, namely in March and September with e-ISSN: 2656-4882 and p-ISSN: 2656-5935.
Arjuna Subject : -
Articles 832 Documents
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Handcrafted Feature Ablation for Batik Nitik Classification Under Provenance-Aware Evaluation Aji Priyambodo; Rizal Isnanto; Ridwan Sanjaya
Journal of Information System and Informatics Vol 8 No 3 (2026): June
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i3.1679

Abstract

This study re-examines Batik Nitik classification using a leakage-safe provenance-aware evaluation protocol to determine which handcrafted descriptors make a substantive contribution to performance and whether saturated results persist after provenance-based partitioning. Batik Nitik 960 was represented using Histogram of Oriented Gradients (HOG), Local Binary Patterns (LBP), Gray-Level Co-occurrence Matrix (GLCM) descriptors, and grayscale intensity moments. Descriptor ablation, classifier benchmarking, cosine-similarity baselines, four-setting leave-one-provenance-group-out sensitivity analysis, and a supplementary image-level split comparison were evaluated using in-pipeline preprocessing. All HOG-containing feature sets achieved 0.9833 cross-validation accuracy and 1.0000 hold-out accuracy. On fused features, SVM, KNN (Euclidean), and KNN (cosine) achieved 1.0000 hold-out accuracy, while Random Forest reached 0.9958. Raw-pixel, HOG-only, and fused-feature cosine baselines also reached 1.0000 hold-out accuracy. A supplementary image-level HOG-SVM split also produced 1.0000 accuracy. This study contributes a provenance-aware benchmark diagnosis for Batik Nitik classification by identifying HOG as the strongest standalone handcrafted descriptor and by cautioning against deployment-ready interpretation of saturated closed-set accuracy.
UTAUT-Based Analysis of Factors Associated with Microsoft Teams Use in Digital Learning among Undergraduate Students Cintya Syarah Azzahra; Jap Tji Beng; Sri Tiatri; Fouad Nagm; Rahmiyana Nurkholiza; Vienchenzia Oeyta Dwitama Dinatha
Journal of Information System and Informatics Vol 8 No 3 (2026): June
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i3.1697

Abstract

This study examined factors influencing Microsoft Teams adoption in digital learning using the Unified Theory of Acceptance and Use of Technology (UTAUT). A quantitative cross-sectional survey was conducted with 268 undergraduate students, and data were analyzed using reliability testing, Confirmatory Factor Analysis (CFA), classical assumption testing, and multiple linear regression. The results showed that Performance Expectancy, Effort Expectancy, and Social Influence significantly influenced Behavioral Intention, while Facilitating Conditions and Behavioral Intention significantly influenced Use Behavior. The model explained 60.2% of the variance in Behavioral Intention and 46.4% of the variance in Use Behavior. CFA demonstrated acceptable fit for most indices, although RMSEA indicated marginal fit. Performance Expectancy was the strongest predictor of Behavioral Intention, whereas Behavioral Intention was the strongest predictor of Use Behavior. Unlike previous studies focusing primarily on Behavioral Intention, this study also examined its relationship with self-reported Use Behavior among Indonesian undergraduates. The findings highlight the importance of usefulness, ease of use, social support, and facilitating conditions in promoting Microsoft Teams adoption for digital learning.

Page 84 of 84 | Total Record : 832

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