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Data : Journal of Information Systems and Management
Published by PT Penerbit Ilmiah Indonesia
ISSN : -     EISSN : 30310008     DOI : https://doi.org/10.61978/data
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Data : Journal of Information Systems and Management with ISSN Number 3031-0008 (Online) published by Indonesian Scientific Publication, is a leading open-access and peer-reviewed scientific journal dedicated to publishing high-quality research in the field of information systems and management. Since its establishment, Data has been committed to advancing knowledge and understanding of the integration between information systems and management in a global context. The journal publishes research articles, technical papers, theoretical studies, and case studies that undergo rigorous peer review to ensure the highest standards of academic integrity and originality.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 5 Documents
 1 
Search results for , issue "Vol. 3 No. 3 (2025): July 2025" : 5 Documents clear
Phishing Email Classification Approach Using Machine Learning Algorithms - A Literature Review Firman; Tukiyat; Wiharjo, Sudarno
Data : Journal of Information Systems and Management Vol. 3 No. 3 (2025): July 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/data.v3i3.692

Abstract

Email phishing is one of the cybersecurity threats that continues to grow, utilizing social engineering to obtain sensitive data. Various machine learning-based approaches have been researched to detect and classify phishing emails. This article presents a literature review of phishing email classification methods, including the K-Nearest Neighbor (KNN) algorithm, Naïve Bayes, Support Vector Machine (SVM), Random Forest, and deep learning-based approaches. The discussion included feature extraction techniques (TF-IDF, Word2Vec, BERT), handling data imbalances, and model performance evaluation. This review identifies current research trends, challenges, and gaps for further research.
Overcoming Barriers to Decision Support Systems in Healthcare, Education, and Public Policy: Toward Inclusive and Ethical Implementation Subekti , Rino
Data : Journal of Information Systems and Management Vol. 3 No. 3 (2025): July 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/data.v3i3.707

Abstract

Decision Support Systems (DSS) are increasingly recognized as vital tools for enhancing organizational decision-making across sectors. This narrative review synthesizes empirical evidence on the effectiveness, challenges, and strategic implications of DSS implementation, focusing on healthcare, education, supply chain, and public policy sectors. By examining these areas, the study highlights sector-specific dynamics and barriers to adoption. Using a systematic narrative approach, the study draws from literature indexed in Scopus, Google Scholar, and Web of Science, applying keyword-based searches and inclusion criteria to select peer-reviewed empirical and theoretical studies published within the last decade. The review finds, for example, that DSS in healthcare reduce sepsis-related mortality by enabling early detection, while in education, DSS support adaptive learning systems that align teaching with student performance data. In supply chains, DSS improve delivery times by up to 30%, and in public policy, they facilitate scenario-based analysis for transparent decision-making. However, systemic barriers such as infrastructure limitations, low digital literacy, and cultural resistance persist, especially in public sector adoption. These barriers impede the full realization of DSS potential and necessitate multi-level interventions. Integration of DSS has shown to not only optimize operational performance but also inform long-term strategic planning and policy development. The discussion underscores the importance of adaptive DSS models, user-centric design, and ethical governance in maximizing system effectiveness. The study concludes that while DSS offer transformative potential, their success depends on addressing institutional readiness and embedding ethical, inclusive frameworks. Future research should prioritize longitudinal studies on DSS adoption in healthcare and education, cross-country comparisons of supply chain DSS, and investigation into governance frameworks that ensure ethical use in public policy
Strategic IT–Business Alignment and Big Data Analytics Capability: A Configurational Approach to Operational Excellence in Manufacturing Lukman
Data : Journal of Information Systems and Management Vol. 3 No. 3 (2025): July 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/data.v3i3.909

Abstract

In the era of Industry 4.0, manufacturing firms face growing pressure to enhance operational performance through digital transformation. Central to this transformation is the strategic alignment between IT capabilities and business objectives, supported by advanced analytics and flexible IT infrastructures. This study investigates how different configurations of Strategic Alignment Maturity (SAMM), Big Data Analytics Capability (BDAC), IT flexibility, and business strategy types influence operational outcomes. Employing fuzzy set Qualitative Comparative Analysis (fsQCA) on data collected from 100 manufacturing firms, the research identifies multiple equifinal pathways to high operational performance, as measured by Overall Equipment Effectiveness (OEE) and SCOR metrics. Two dominant configurations emerge from the analysis. The first (R1) combines high levels of SAMM, IT flexibility, BDAC, and a Prospector strategy, highlighting a proactive, innovation oriented approach to operational excellence. The second configuration (R4) achieves similar performance through a different route leveraging BDAC, an Analyzer strategy, and strong CIO–business collaboration even in the absence of mature alignment structures. These results affirm that both alignment driven and analytics driven models can yield superior outcomes depending on organizational context and strategic orientation. The study contributes to the literature by demonstrating that high operational performance does not rely on a single universal model, but rather on the strategic orchestration of complementary capabilities. It also shows the effectiveness of fsQCA in uncovering complex causal relationships within organizational systems. Practically, the findings encourage manufacturing leaders to assess and tailor their alignment, analytics, and IT strategies according to their operational priorities and industry dynamics.
Digital Reform and Civil Service Performance: Empirical Evidence from the Implementation of SIASN, MyASN, and MOLA in Indonesia Suroso, Jarot Sembodo; Barisan
Data : Journal of Information Systems and Management Vol. 3 No. 3 (2025): July 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/data.v3i3.925

Abstract

This study evaluates the impact of integrated digital personnel systems namely SIASN, MyASN, and MOLA on administrative efficiency within Indonesia’s civil service. These platforms were introduced as part of a broader e government reform initiative designed to simplify civil servant workflows, reduce delays, and improve transparency. This study specifically evaluates whether the systems shorten turnaround time (TAT) for services including promotions, retirements, and inter-agency transfers. Employing a Difference in Differences (DiD) approach, this research analyzes panel data from regional civil service offices, comparing outcomes in treated and control regions before and after the implementation of digital systems in late 2022. Data sources include timestamped service records from MOLA, performance reports (LKjIP and LAKIP), and SPBE index scores as a proxy for digital readiness. Key outcomes assessed include average TAT and the percentage of services completed within national performance benchmarks. The findings reveal a statistically significant reduction in TAT across all service categories in treated regions. Retirement processing times dropped by an average of 3.4 days, while promotion and transfer services saw reductions of 1.7 and 2.0 days respectively. The percentage of on time promotions increased by 26.4%. Results were more pronounced in regions with higher SPBE scores, underscoring the importance of institutional digital capacity. Robustness checks affirmed the reliability of the findings across various model specifications. The study concludes that digital personnel systems substantially enhance administrative performance when supported by institutional capacity and strategic implementation frameworks. These findings provide actionable insights for policymakers seeking to scale digital reforms across the public sector. By reinforcing efficiency, accountability, and responsiveness, integrated systems represent a critical step toward modernizing governance in Indonesia.
Task Aligned Technology: Enhancing Cross Unit Collaboration in Remote Work Environments Maulidiyah, Ummi Masrufah; Silvanie, Astried; Sugianto
Data : Journal of Information Systems and Management Vol. 3 No. 3 (2025): July 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/data.v3i3.1089

Abstract

The growing prevalence of remote and hybrid work models has transformed how organizations coordinate tasks and collaborate across functional units. This study investigates whether IT media fit moderates the relationship between remote work intensity and cross unit collaboration. Drawing on Media Synchronicity Theory (MST), the research posits that communication media must align with task requirements particularly synchronicity needs to enhance collaboration outcomes. A quasi experimental, longitudinal design was used, analyzing weekly team level data from digital trace logs (Slack, Microsoft Teams) and surveys assessing remote work intensity and IT media alignment. The study employed Generalized Linear Mixed Models (GLMM) with interaction terms to evaluate the moderating effect of IT media fit. Key findings indicate that remote work alone does not significantly improve collaboration metrics such as network centrality or cross functional reply rates. However, in conditions of high IT media fit, remote work intensity positively correlates with more robust cross unit collaboration. These results were robust across multiple model specifications and validated through lagged temporal analysis, bias checks, and alternative statistical techniques. This research extends MST by incorporating the emotional and contextual dimensions of digital communication tools and emphasizing the need for tool task synchronicity in remote settings. The study provides actionable recommendations for organizations, including aligning communication tools with specific task types, training teams in digital collaboration practices, and designing adaptive communication policies. As digital collaboration becomes central to modern organizational life, the strategic fit between media and task emerges as a vital determinant of remote work effectiveness.

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