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Integrated System and Management Technology
Published by Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia
ISSN : -     EISSN : 31239811     DOI : 10.66472
Core Subject :
Aims This journal focuses on the integration of information technology and management practices to enhance organizational performance, governance, and strategic decision-making in digital environments. Scope IT governance and IT service management Enterprise architecture and integrated systems Technology and innovation management Decision support and executive information systems ERP, CRM, and supply chain systems Digital enterprise and smart organization models Risk management and technology compliance
Arjuna Subject : -
Articles 9 Documents
 1 
An Integrated Framework of Enterprise Architecture and Artificial Intelligence for Optimizing Strategic Decision Making in Digital Service Oriented Organizations Imeldawaty Gultom; Dedi Candro Parulian Sinaga; Safrizal Safrizal
Integrated System and Management Technology Vol. 1 No. 1 (2026): January: Integrated System and Management Technology
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/ismat.v1i1.5

Abstract

This research explores the integration of Enterprise Architecture (EA) and Artificial Intelligence (AI) to optimize strategic decision-making in digital service-oriented organizations. These organizations often face challenges such as fragmented decision-making due to disconnected IT systems and limited data-driven insights. The objective of the study is to develop an integrated framework that combines EA and AI to enhance decision-making accuracy, operational efficiency, and strategic alignment. The study employs design science research methodology, involving the development of the framework, expert validation, and testing in simulated organizational scenarios. The findings reveal that the integrated framework improves decision-making by providing real-time, data-driven insights, predictive analytics, and better alignment with organizational goals. AI's role in analyzing large datasets and generating actionable insights allows decision-makers to anticipate future trends and make more informed decisions. The framework significantly outperforms traditional EA approaches, particularly in terms of predictive decision support and adaptive intelligence. The study concludes that the integration of EA and AI provides a robust solution for organizations looking to improve strategic decision-making, enhance operational efficiency, and stay competitive in dynamic business environments.
Examining the Role of Information Technology Governance in Enhancing Risk Management Performance and Regulatory Compliance in Multinational Digital Enterprises Gunawan Prayitno; Ronaldo Aprili
Integrated System and Management Technology Vol. 1 No. 1 (2026): January: Integrated System and Management Technology
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/ismat.v1i1.7

Abstract

This study investigates the role of Information Technology (IT) governance in enhancing risk management performance and ensuring regulatory compliance within multinational digital enterprises. As digital transformation continues to reshape the global business landscape, organizations face increasing challenges in managing technological risks and complying with complex regulatory requirements across various jurisdictions. The study adopts a quantitative approach, using a survey methodology to collect data from senior IT and compliance managers in multinational digital enterprises. The survey focuses on how IT governance frameworks, such as COBIT 2019 and ISO 27000, are utilized to align IT strategies with business objectives, mitigate risks, and maintain regulatory compliance. The findings indicate that organizations with well-established IT governance structures are better positioned to proactively identify and mitigate risks, ensuring greater consistency in meeting regulatory requirements. These organizations demonstrate improved risk management effectiveness, especially concerning cybersecurity, data privacy, and compliance with global regulations like GDPR. In contrast, organizations with ad hoc or decentralized governance structures struggle with fragmented risk management and compliance efforts. The study further highlights the importance of integrating IT governance frameworks with internal audit functions, specifically the Chief Audit Executive (CAE), to enhance cybersecurity resilience and ensure compliance with global standards. This research contributes to the literature by providing empirical evidence on the integration of IT governance, risk management, and regulatory compliance in multinational enterprises. It also highlights the need for a structured and systematic approach to IT governance to improve organizational performance in managing risks and ensuring consistent regulatory adherence. The study offers practical insights for organizations looking to optimize their IT governance structures in the face of rapid digital transformation.
Implementing Integrated Customer Relationship Management and Enterprise Resource Planning to Drive Customer Experience Innovation in Modern Digital Enterprises Sudirwo Sudirwo; Didik Sofian Hariyadi; Rusobby Andika Kumajaya
Integrated System and Management Technology Vol. 1 No. 1 (2026): January: Integrated System and Management Technology
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/ismat.v1i1.9

Abstract

The integration of Customer Relationship Management (CRM) and Enterprise Resource Planning (ERP) systems has emerged as a critical strategy for modern digital enterprises aiming to enhance customer experience and operational efficiency. This study examines the impact of CRM-ERP integration on customer satisfaction, personalized service, and organizational responsiveness. By adopting a mixed-methods approach, this research combines quantitative customer data analysis and qualitative managerial interviews to assess the benefits and challenges of CRM-ERP integration. Key findings highlight significant improvements in customer experience, with increased satisfaction and personalized interactions facilitated by a unified view of customer data. Operational efficiencies were also realized through streamlined processes, better alignment of departments, and enhanced decision-making based on real-time, data-driven insights. Despite these positive outcomes, challenges such as system integration complexities, data fragmentation, and resistance to change were identified, which hindered the speed of integration and full utilization of the systems. This study demonstrates that CRM-ERP integration provides a competitive advantage by improving both customer service and business agility, particularly in industries undergoing digital transformation. For digital enterprises, integrating these systems is crucial for maintaining a seamless customer experience across various touchpoints and achieving greater operational effectiveness. The paper concludes by suggesting future research on the long-term impact of CRM-ERP integration on customer loyalty, business growth, and the potential role of emerging technologies like AI and blockchain in further enhancing these systems.
The Impact of Information Technology Driven Innovation Management on IT Service Management Effectiveness and Competitive Value Creation in Smart Organizations Priyo Wibowo; Sunarmi Sunarmi
Integrated System and Management Technology Vol. 1 No. 1 (2026): January: Integrated System and Management Technology
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/ismat.v1i1.11

Abstract

This study examines the impact of IT-driven innovation management on IT service effectiveness and competitive value creation within smart organizations. As digital transformation accelerates across industries, organizations are increasingly leveraging advanced IT solutions to enhance service delivery, responsiveness, and customer satisfaction. While traditional IT service management (ITSM) models focus on efficiency and structured processes, the integration of innovation management introduces new opportunities to improve service quality and operational agility. Through a quantitative research design, this study employs regression modeling to assess the relationship between IT-driven innovation management and two key outcomes: IT service effectiveness and competitive value creation. Data were collected from 100 technology-intensive organizations that actively integrate innovation into their IT service management processes. The results demonstrate that IT-driven innovation significantly enhances service quality, customer satisfaction, and organizational competitiveness. Furthermore, a curvilinear relationship was identified, indicating that while moderate innovation leads to improved outcomes, excessive innovation may have diminishing returns. These findings highlight the importance of balancing innovation efforts with business goals to achieve optimal performance. The study also compares innovation-driven IT service management with traditional models, illustrating how innovation fosters agility, responsiveness, and long-term value creation. The implications for smart organizations are clear: integrating innovation into IT service management is essential for maintaining a competitive edge in the rapidly evolving digital landscape. Future research should explore the long-term impact of innovation management on organizational sustainability and growth, considering external factors such as market volatility and technological disruptions.
Executive Decision Support System Implementation Strategies Based on Big Data Analytics to Improve Operational Efficiency and Corporate Governance in Global Digital Enterprises Asro Asro; Solihin Solihin; Irlon Irlon
Integrated System and Management Technology Vol. 1 No. 1 (2026): January: Integrated System and Management Technology
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/ismat.v1i1.13

Abstract

This study explores the transformative role of big data-driven Decision Support Systems (DSS) in global digital enterprises, particularly focusing on their impact on operational efficiency and corporate governance. By leveraging big data analytics, DSS offer organizations the tools to process vast amounts of real-time data, enabling executives to make more informed decisions that optimize resources, improve productivity, and reduce operational costs. The research highlights the integration of predictive analytics, machine learning, and real-time data processing within DSS, which allows businesses to gain strategic insights and anticipate market trends. Furthermore, the study emphasizes the significant role of DSS in enhancing corporate governance, improving transparency, accountability, and compliance with regulations. These systems foster better decision-making processes, which contribute to building trust among stakeholders and ensuring long-term organizational success. However, the study also identifies several challenges in implementing big data-driven DSS, including data management complexities, technological integration difficulties, and the need for skilled personnel. Despite these challenges, the findings demonstrate that big data-driven DSS are pivotal in driving competitive advantage, operational optimization, and governance improvements. The research concludes with actionable recommendations for executives to adopt and implement big data-driven DSS, emphasizing the importance of continuous support, training, and system integration. The study also suggests future research directions, including exploring the integration of emerging technologies like AI and IoT into DSS and assessing their long-term impact on sustainability and corporate governance.
Developing an AI-Driven Prescriptive Framework for Orchestrating MSME Supply and Demand: Integration of Hyper-Local Community Engagement Signals Nanang Abdurahman; Zainal Arifin Hasibuan; Irawan Afrianto; Ifan Dwiguna
Integrated System and Management Technology Vol. 1 No. 2 (2026): July: Integrated System and Management Technology
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/ismat.v1i2.389

Abstract

Micro, Small, and Medium Enterprises (MSMEs) face significant challenges in balancing supply and demand amidst the rapid volatility of the digital economy era. This condition is primarily driven by conventional, reactive decision-making and a failure to utilize social media data beyond mere marketing metrics, resulting in operational inefficiencies such as overstocking or stockouts. This research aims to address this gap by developing an Artificial Intelligence-Based Prescriptive Framework for MSME Supply-Demand Orchestration. Adopting a Design Science Research (DSR) methodology, specifically focusing on problem identification, objective definition, and conceptual artifact design, this study synthesizes insights from 100 recent articles (2020-2025). The proposed conceptual artifact introduces a novel three-tier system architecture: a Sensing Layer utilizing NLP (BERT) to extract hyper-local community engagement signals into a Social Engagement Index (SEI), a Reasoning Layer employing a Hybrid Neuro-Fuzzy engine to accommodate MSME data sparsity, and a Prescriptive Actuation Layer. The findings present a mechanism that transforms unstructured qualitative social sentiment into quantitative, actionable logistical commands (e.g., "Priority Restock"), demonstrating superiority over existing predictive or macro-level models by offering a closed-loop, hyper-local solution. In conclusion, this research successfully formulates a framework that shifts MSME management paradigms from being purely reactive to actively responsive to social signals, theoretically expanding Social-SCM integration and practically offering a pathway to mitigate inventory risks and enhance economic sustainability.
The AHP-TOPSIS Integration of a Decision Support System to Analyze and Enhance Student Engagement Based on Cus-tomer Relationship Management Approach Trias Pungkur Kusumaningrum; Andjar Hernanto; Danik Riawati
Integrated System and Management Technology Vol. 1 No. 2 (2026): July: Integrated System and Management Technology
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/ismat.v1i2.434

Abstract

Student engagement has become an important issue in higher education because it is closely related to academic achievement, learning effectiveness, and student retention. In digital learning environments, institutions require a systematic and data-driven approach to evaluate student engagement and support strategic academic decision-making. However, most previous studies still focus on descriptive and predictive analysis without providing structured decision support mechanisms integrated with relationship management strategies. Therefore, this study aims to develop an integrated Decision Support System (DSS) by combining the Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods within a Customer Relationship Management (CRM) approach to analyze and enhance student engagement. The study was conducted at Politeknik AKBARA Surakarta involving 47 students as respondents. The evaluation criteria consisted of Behavioral Engagement, Emotional Engagement, Cognitive Engagement, LMS Interaction, and Academic Participation. The AHP method was applied to determine the priority weights of the criteria, while TOPSIS was used to rank and classify student engagement levels. The results showed that the proposed framework successfully classified students into high, medium, and low engagement categories objectively and systematically. The CRM approach further translated these classifications into strategic academic actions such as retention programs, engagement improvement, and intensive intervention strategies. The integration of AHP-TOPSIS and CRM provides a comprehensive framework for transforming student engagement data into actionable academic decision support, enabling institutions to implement more personalized, adaptive, and data-driven student engagement management.
Integrated and Spatiotemporal Predictive Data-Driven Narcotics Intelligence Ecosystem: Governance, Interoperability, and Analytics Pipeline for Evidence-Based Policy : Case Study: BNNP West Java, Indonesia Luki Ishwara; Agus Nursikuwagus; Ednawati Rainarli; Zainal Arifin Hasibuan; Sri Supatmi
Integrated System and Management Technology Vol. 1 No. 2 (2026): July: Integrated System and Management Technology
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/ismat.v1i2.436

Abstract

Across BNN, police, health, corrections, and local government, Indonesia's crossagen cynarcotics control produces a lot of data yet fragmented, limiting timely identification of abuse patterns,hotspots, and resource requirements. It aims to bridge the gap between international breakthroughson the use of machine-learning–based monitoring and optimization under uncertainty and underdeveloped provincial integration of governance, interoperability, and predictive analytics in the public sector. It is about designing and assessing an integrated spatiotemporal predictive, datadriven narcotics intelligence ecosystem for BNNP West Java. The approach combines iterative information systems engineering with an embedded case study and a mixed-methods evaluation covering seven phases: requirements structuring; data governance and quality; federated/hybrid interoperability and Privacy-Preserving Record Linkage; spatiotemporal predictive pipelines with both baseline and advanced models and anomaly detection; hotspot and risk mapping; early warning and situational dashboards linked to operational protocols; and implementation assessment with institutional learning.Evaluation utilizes quantitative measurements for data quality and model performance (including lead time and false-alarm considerations) and qualitative findings evaluating governance readiness and usability. Expected outputs can comprise a four-pillar framework bridging governance and policy impact, replicable artefacts to be deployed at the provincial level, and implications for evidence-based narcotics policy under national digital-government agendas, with considerations for data-access andprivacy limitations.
A Design Science Roadmap for Auditable Ocular Disease Classification: Evidence Mapping of AI Governance Gaps Rizal Rachman
Integrated System and Management Technology Vol. 1 No. 2 (2026): July: Integrated System and Management Technology
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/ismat.v1i2.442

Abstract

The integration of Artificial Intelligence (AI) into ocular diagnostics has led to substantial improvements in predictive accuracy. However, a persistent gap remains between technical performance and clinical accountability. The present study addresses the "accuracy trap" and the lack of transparency in current deep learning models for ocular disease classification. The objective of the research is twofold: firstly, to identify methodological deficiencies in extant literature and, secondly, to propose a standardised evaluative framework to ensure model auditability. A systematic evidence mapping (SEM) approach, combined with design science research methodology (DSRM), was utilised to scrutinise 10 high-impact Scopus-indexed studies published between 2023 and 2026. The findings reveal a critical "predictive validity gap," where 80% of the evidence base relies on aggregate accuracy while 90% remains "black box" without functional Explainable AI (XAI) layers. The synthesis of these gaps resulted in the formulation of a conceptual roadmap that mandated multi-metric evaluation, incorporating Cohen's Kappa, and pathophysiological traceability. In conclusion, this research establishes that clinical deployment of AI must transition from model-centric success to a governance-oriented paradigm that prioritises decision utility and auditable audit trails. This roadmap provides a rigorous blueprint for the future implementation of transparent and accountable medical AI systems.

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