Article Per Year (5 Year)
p-Index From 2021 - 2026
0.562
P-Index
This Author published in this journals
All Journal Aptisi Transactions on Management ADI Bisnis Digital Interdisiplin (ABDI Jurnal)
Kristina Vaher
ILearning Incorporation
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Library & Information Science

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Design of Campus Activity Feedback Information System Based on Content Management System (CMS) Muhtarom Muhtarom; Iqbal Mansis; Meri Mayang Sari; Ari Asmawati; Kristina Vaher
ADI Bisnis Digital Interdisiplin Jurnal Vol 7 No 1 (2026): ADI Bisnis Digital Interdisiplin (ABDI Jurnal)
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b90nss42

Abstract

The management of student activity evaluation often faces significant efficiency challenges due to feedback collection methods that are still manual, fragmented, and not well integrated, resulting in slow data recapitulation, high potential for data inconsistency, and difficulties in tracing historical evaluation archives, which ultimately weakens the effectiveness of decision-making in quality assurance processes. To address these issues, this study aims to design and develop a feedback information system based on the WordPress Content Management System (CMS), chosen for its flexibility, ease of implementation, extensibility, and capability to centralize data management without requiring complex technical infrastructure. The system development adopts the Waterfall model, consisting of systematic stages including requirements analysis, system design, implementation, and testing, ensuring that the development process is structured and measurable. The analysis stage identifies user needs and system requirements through observation and document review, while the design stage focuses on developing a user-friendly interface, structured data storage, and role-based access control for administrators and users. During implementation, WordPress is configured and customized through plugins and online feedback forms that enable automatic data processing and centralized archiving. Functional testing simulations demonstrate that the system operates according to its specifications and is capable of supporting online data input, automatic report generation, and efficient data management. Preliminary evaluation results indicate that the proposed system can reduce data recapitulation time by up to 70% compared to conventional methods, making it a practical solution for supporting the digitalization of quality assurance in student activity management.
Equity and Government Bond Relationship in Indonesia During Covid Pandemic Gracia Shinta S. Ugut; Liza Handoko; Kristina Vaher
APTISI Transactions on Management (ATM) Vol 10 No 2 (2026): ATM (APTISI Transactions on Management: May)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tf8nn721

Abstract

This study extends prior Covid-19 finance literature by examining the dynamic relationship between Indonesian equity returns and sovereign benchmark bond returns using daily data across two pandemic waves. Unlike previous studies focusing primarily on developed markets or conventional flight-to-safety behavior, this study provides evidence that government bonds in emerging markets may temporarily exhibit equity-like risk characteristics during pandemic-induced fiscal stress. Specifically, the findings show that equity market performance is positively correlated with government bond returns in Indonesia during the two waves of the Covid 19, as opposed to the findings from previous studies when there were financial crises, and also the results show negative correlation between the government bond return and the spread of the Credit Default Swap. Furthermore, this study examines the impact of the Covid pandemic to the local Indonesian long-term and medium-term benchmark bonds after applying the international risk factor variable to the model. The results show shifting investors’ attention from the international risk factors to the local risk factors in both medium and long tenor of the bonds during the pandemic period. Overall, this study highlights how pandemic-induced fiscal uncertainty alters stockbond dynamics in emerging markets and challenges conventional safe-haven assumptions regarding sovereign bonds.
Audit Driven Evaluation of Carrier Style Memory Malware Detection Under Obfuscation and Adversarial Attacks Syamsu Hidayat; Kusrini Kusrini; Ema Utami; Arief Setyanto; Kristina Vaher
APTISI Transactions on Management (ATM) Vol 10 No 2 (2026): ATM (APTISI Transactions on Management: May)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/dp3mdf65

Abstract

This study evaluates Carrier-style memory malware detection under obfuscation using a reproducible, audit-driven protocol for verifiable reporting. We reproduce a stacking pipeline (Naive Bayes, Random Forest, Decision Tree with a Logistic Regression meta-learner) and benchmark it against strong single-model baselines. To limit leakage, we apply exact deduplication, train-only preprocessing, and group-disjoint splitting with explicit overlap checks, and we report dataset difficulty diagnostics to interpret near-ceiling results. Transfer is tested via cross-collection evaluation on the shared feature intersection between Obfuscated MalMem2022 and MemMalDet 2024, separating a low-shift validation setting from a higher-shift stress setting to keep generalization claims bounded. Robustness is assessed under a feasibility-preserving feature-space threat model with empirical bounds, non-negativity, and integer rounding, using a coordinate-search attack on the clean-correct subset across L0 budgets B=1,3,5, and 10 with confidence intervals. On obfuscated MalMem2022, Random Forest achieves 99.99% Accuracy, 99.99% F1, and 1.00 AUC, while the Carrier-style stack reaches 99.92% Accuracy, 99.92% F1, and 1.00 AUC, with no meaningful improvement over the best single model. Cross-collection validation yields F1 = 99.98 and AUC = 1.0, consistent with low-shift stability under aligned features rather than broad domain generalization. At B=10, ASR is 0.03 (95% CI: 0.0138–0.0639), and baseline defenses show clean-versus-robust trade-offs without consistent ASR reduction. We release four reusable artifacts an audit table, a leakage ablation matrix, a shift-aware cross-collection report, and robustness curves with confidence intervals.
Co-Authors Ari Asmawati Arief Setyanto Ema Utami Gracia Shinta S. Ugut Iqbal Mansis Kusrini Kusrini Liza Handoko Meri Mayang Sari Muhtarom Muhtarom Syamsu Hidayat