Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer TIERS Information Technology Journal
Dandy Pramana Hostiadi
Institut Teknologi dan Bisnis STIKOM Bali, Indonesia
Computer Science & IT

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Evaluating Lecturer Satisfaction on Academic Information System Using Usability and EUCS at Bandung University of Technology Sela Octaviani; Evi Triandini; Dandy Pramana Hostiadi
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 25 No. 1 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v25i1.4844

Abstract

Academic Information Systems play a crucial role in supporting academic data management, administrative processes, and informed decision-making within higher education institutions. Despite their widespread adoption, the extent to which these systems effectively meet the needs and expectations of lecturers, their primary users, remains insufficiently explored. Understanding user satisfaction is critical, as it directly influences system acceptance, continued usage, and overall institutional performance. This study aims to evaluate lecturer satisfaction with Academic Information Systems at Bandung University of Technology by integrating two complementary evaluation methods, the System Usability Scale and End User Computing Satisfaction. The integration of these methods enables a more holistic assessment by combining usability measurements with multidimensional user satisfaction indicators. The findings reveal an exceptionally high SUS score of 99.94, classified as Best Imaginable, indicating that lecturers perceive the system as highly usable, intuitive, and supportive of their academic tasks. The EUCS analysis identifies Accuracy, Format, and Ease of Use as significant factors influencing lecturer satisfaction. These variables demonstrate the importance of accurate and reliable information, a well-structured interface, and system features that facilitate efficient task completion. The combined results highlight specific areas requiring strategic improvement, particularly in maintaining data accuracy, enhancing interface design consistency, and strengthening overall usability to accommodate users’ academic workflows. Theoretically, it demonstrates the added methodological robustness gained from combining SUS and EUCS in evaluating academic information systems, thereby ensuring more substantial alignment with user
Safety-Oriented Air Quality Index Classification for Imbalanced Data Using Optimized Boosting Models with Optuna and Oversampling Made Yudi Dwipayana; Gede Angga Pradipta; Dandy Pramana Hostiadi
TIERS Information Technology Journal Vol. 7 No. 1 (2026)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/tiers.v7i1.7558

Abstract

Air Quality Index (AQI) classification is essential for communicating environmental health risks. However, hazardous air conditions occur far less frequently than normal conditions, challenging conventional classification models. This study investigates multi-class AQI classification using the "Global Air Quality 2025" dataset, comprising 52,704 observations with an extreme class imbalance ratio of approximately 1:173. Under such conditions, conventional accuracy metrics often mask systemic failures in detecting critical minority classes. To address potential data leakage present in previous approaches, this research implements a rigorous cross-validation architecture combined with an independent 20% hold-out test set. The methodology employs an Ablation Study to systematically isolate the impacts of Optuna hyperparameter tuning guided by Macro F1-Score and oversampling techniques (SMOTE and ADASYN). The results demonstrate that the proposed Hybrid-SMOTE LightGBM configuration successfully balances hazard detection sensitivity with global stability. On the unseen hold-out set, the optimal model achieved a Macro F1-Score of 0.8079, an accuracy of 92.80%, and a ROC-AUC of 0.9847. Crucially, the model delivered a 65.12% recall for the critical Unhealthy minority class, a nearly 40% improvement over the baseline. Error profile analysis confirmed the model's safety-oriented robustness, as 97.6% of peak hazardous events were either accurately classified or safely constrained to the adjacent warning category, minimizing catastrophic misclassifications. These findings prove that reliable detection of environmental hazards requires safety-oriented per-class evaluation and strict validation frameworks, as reliance on aggregate global metrics leads to dangerously misleading performance assessments.
Co-Authors Evi Triandini Gede Angga Pradipta Made Yudi Dwipayana Sela Octaviani