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Information System Analysis, Design and Development
Published by Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia
ISSN : -     EISSN : 31239781     DOI : 10.66472
Core Subject :
Information System Analysis, Design and Development is a peer-reviewed academic journal that publishes high-quality research on the analysis, design, development, and implementation of information systems that support organizational processes, decision-making, and digital transformation across various sectors, covering topics such as information systems analysis and modeling, systems design methodologies, business process optimization, enterprise systems, information systems governance and alignment, organizational innovation, and the application of information systems in public institutions, education, healthcare, and small and medium-sized enterprises (SMEs). The journal is published in January, April, July, and October.
Arjuna Subject : -
Articles 21 Documents
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The rapid advancement of digital Analysis of the Use of Management Information Systems in the Marketing Strategy of Buketbyysmn in Samarinda City Based on the AIDA Model Yasmin Khairunnisa; Hamdani Hamdani
Information System Analysis, Design and Development Vol. 1 No. 3 (2026): July: Information System Analysis, Design and Development
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/isadd.v1i3.238

Abstract

This study examines the role of Management Information Systems (MIS) in supporting digital marketing activities within Micro, Small, and Medium Enterprises (MSMEs), with a case study of Buketbyysmn, a small business operating in the bouquet and gift industry in Samarinda, Indonesia. The rapid growth of social media-based business practices has encouraged MSMEs to adopt digital platforms. However, many businesses still face challenges in understanding how these systems influence customer behavior and decision-making processes. Therefore, this research aims to analyze how MIS is implemented in Buketbyysmn and how it supports customer engagement through the AIDA (Attention, Interest, Desire, Action) model. This study employs a qualitative case study approach, using semi-structured interviews and observational analysis of the business’s Instagram account as the primary data sources. The analysis focuses on how digital platforms such as Instagram and WhatsApp function as informal MIS tools in supporting marketing and transaction processes. The findings reveal that Instagram plays a major role in generating customer Attention and Interest through visual content, promotional strategies, and product information dissemination. Meanwhile, customer Desire is influenced by pricing strategies, testimonials, and social proof, while Action is facilitated through WhatsApp-based communication for ordering and transaction completion. The study also finds that simple MIS tools such as social media insights and manual order tracking are effectively used to manage customer interactions. In conclusion, MIS implementation in MSMEs does not require complex systems, as lightweight digital platforms can function as an integrated marketing and operational system. Keywords: Management Information System; Digital Marketing; MSME; AIDA Model; Social Media Marketing; Instagram; Qualitative Study
Factors Influencing the Adoption of Management Information Systems in SMEs: A Systematic Literature Review Annisa Fazzahra; Gusti Noorlitaria Achmad
Information System Analysis, Design and Development Vol. 1 No. 3 (2026): July: Information System Analysis, Design and Development
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/isadd.v1i3.283

Abstract

This study examines the role of Management Information Systems (MIS) in improving the performance and competitiveness of Micro, Small, and Medium Enterprises (MSMEs) in the digital era. MSMEs face various challenges, including limited operational efficiency, manual data processing, low digital adoption, and increasing market competition. Therefore, this study aims to analyze the effectiveness of MIS implementation and identify key factors influencing its adoption in MSMEs. The research employs a Systematic Literature Review (SLR) approach following PRISMA guidelines, with data collected from academic databases such as Google Scholar using the Publish or Perish tool. From an initial pool of 400 articles, 45 relevant studies were selected for in-depth analysis. The findings indicate that MIS implementation significantly improves operational efficiency, data accuracy, and decision-making processes, while also enhancing marketing performance and customer engagement. The systems identified include operational-based systems, marketing and CRM systems, strategic and integrated systems, user-centered systems, and technology-based systems such as cloud and mobile applications. Additionally, the study finds that system usability, compatibility, and perceived usefulness are critical factors influencing user acceptance and successful implementation. In conclusion, MIS plays a vital role in supporting MSME digital transformation and increasing business competitiveness; however, challenges such as limited digital literacy, infrastructure, and integration capabilities remain. Future research is recommended to explore advanced technologies and broader empirical validation to strengthen MIS adoption in MSMEs.
Hybrid DTW-ARIMA Model for Rice Price Forecasting: An Indonesian Case Study Maria Sunarti Ekowati Ekowati; Nurul Hidayat; Ahmad Fauzi; Kristyana Dananti; Budi Al Amin; Rina Oktiyani; Rousyati Rousyati; Puji Widodo
Information System Analysis, Design and Development Vol. 1 No. 4 (2026): October: Information System Analysis, Design and Development
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/isadd.v1i4.355

Abstract

Rice, as a strategic commodity in Indonesia, experiences significant fluctuations that affect economic stability and public welfare. This raises challenges in food policy planning, particularly in achieving accurate price forecasting. The research problem addressed is how to improve rice price forecasting accuracy using time series clustering capable of capturing complex interregional patterns. The study is limited to monthly rice price data over the past five years. To solve this problem, a hybrid model integrating Dynamic Time Warping (DTW) and Autoregressive Integrated Moving Average (ARIMA) is proposed. DTW measures similarity among time series patterns, while ARIMA constructs predictive models based on historical data. The objective is to produce more accurate and stable forecasts compared to single-method approaches. The urgency lies in its contribution to national food policy and food security. The novelty compared to previous studies is the integration of DTW-ARIMA within a time series clustering framework, rarely applied to food commodities in Indonesia. Experimental results indicate that the hybrid DTW-ARIMA model achieves lower mean absolute percentage error (MAPE) than conventional methods. The expected output is a predictive model that can be implemented as a data-driven decision support system for national food policy.
Integration Supply Chain Management, Customer Rela-tionship Management and Accounting Information Systems based Machine Learning to Enhance the Competitive Ad-vantage of MSMEs Dony Firdaus; Zainal Hasibuan; Agus Nursikuwagus; Wartika Wartika
Information System Analysis, Design and Development Vol. 1 No. 4 (2026): October: Information System Analysis, Design and Development
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research examines the integration of Supply Chain Management (SCM), Customer Relationship Management (CRM), and Accounting Information Systems (AIS) based on Machine Learning (ML) to enhance the competitive advantage of SMEs, focusing on three questions: (RQ1) the relevant integration architecture, (RQ2) the integration mechanisms, and (RQ3) its impact on competitiveness. The study uses a Systematic Literature Review (SLR) with the PRISMA 2020 method and bibliometric analysis thru Biblioshiny on Scopus-indexed publications from 2020 to 2025. From the initial 2,923 documents, after deduplication, title/abstract screening, and full-text eligibility, 255 articles were designated as the corpus for analysis. The mapping results show rapid growth (annual growth rate of 44.35%) and a concentration of publications in 2023–2024, indicating the topic of intelligent system integration for SMEs as an emerging research front. The thematic and co-occurrence mapping confirms the interconnection of supply chain, customer/marketing, accounting, and AI/ML themes, with the dominant central outcomes being business/firm/financial performance, competitiveness, and competitive advantage. However, the distribution of domain combinations shows that research is still dominated by single domains, making the simultaneous integration of SCM, CRM and AIS based ML a major gap. The study concludes the need for a modular, cost-effective, and easily adoptable integration architecture, with a focus on data standardization, lightweight cloud modules, and strengthening the competencies of MSME actors, as well as encouraging further research for implementable artifacts and more measurable impact evaluations.
Conversational Executive Information System in Higher Education Institution: A Systematic Literature Review Andri Heryandi; Zainal Arifin Hasibuan; Bobby Kurniawan; Sri Supatmi
Information System Analysis, Design and Development Vol. 1 No. 3 (2026): July: Information System Analysis, Design and Development
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/isadd.v1i3.412

Abstract

Higher education management is evolving from functionally isolated information systems toward integrated and augmented intelligence frameworks. While dashboard-based Executive Information Systems (EIS) effectively support routine reporting, they remain limited in contextual awareness and analytical capability for complex strategic decision-making. This study aims to explore the evolution of Executive Information Systems in higher education toward a conversational paradigm by identifying the limitations of conventional EIS and examining executive information needs and interaction patterns. This research employs a Systematic Literature Review (SLR) approach to identify, evaluate, and synthesize relevant peer-reviewed studies, following a structured protocol that includes the definition of research questions, database selection, inclusion and exclusion criteria, and systematic analysis. The selected literature focuses on Executive Information Systems, agent-based architecture, Large Language Model (LLM) integration, and augmented intelligence approaches that combine data-driven and model-based techniques. The findings reveal that existing EIS implementations are predominantly constrained by static dashboards and limited interaction mechanisms. The analysis further highlights emerging trends in conversational interaction, intelligent data processing, and augmented analytics, as well as key technological, architectural, security, and organizational considerations influencing the adoption of conversational approaches. This study demonstrates that a conversational paradigm offers a promising direction for advancing Executive Information Systems in higher education by enhancing executive access to contextualized information and supporting more effective strategic decision-making.
Decision Support System for Determining Salary Increases Based on Workload Using the AHP Method Fahrul Musyafa; Yosia Jeremy Ferdy Tumbel; Heny Pratiwi
Information System Analysis, Design and Development Vol. 1 No. 3 (2026): July: Information System Analysis, Design and Development
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/isadd.v1i3.415

Abstract

Determining salary increases is a crucial policy in human resource management that directly influences employee retention and organizational stability. However, this process is frequently marred by managerial bias and a lack of transparency. This study develops a Decision Support System (DSS) specifically targeted at providing a justifiable framework for salary adjustments based on objective workload metrics. By employing the Analytic Hierarchy Process (AHP), the system decomposes the decision problem into a structured hierarchy, prioritizing "Hours per Week" as the primary workload indicator. The model was validated using a comprehensive salary prediction dataset. Results indicate that the Workload criterion achieved the highest weight (0.648), significantly outweighing Education (0.229) and Experience/Age (0.122). Comparative analysis with a Random Forest classification model (87.3% accuracy) demonstrates that while machine learning excels in predictive performance, the AHPbased DSS provides the essential transparency required for ethical HR interventions. This system targets the reduction of perceived unfairness, thereby fostering a more meritocratic organizational culture.
Digital Transformation and Data-Driven Decision Making in Marketing: A Literature Review Irwan Irwan; Hamdani Hamdani; Kusnadi Kusnadi; Erni Wahyuni
Information System Analysis, Design and Development Vol. 1 No. 3 (2026): July: Information System Analysis, Design and Development
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/isadd.v1i3.418

Abstract

Digital transformation has become an important factor influencing marketing strategies and organizational decision-making processes in the digital era. The development of technologies such as artificial intelligence, big data analytics, machine learning, and digital platforms has encouraged organizations to shift from intuition-based decision making toward data-driven decision-making approaches. However, despite rapid technological advancement, many organizations still face challenges related to data quality, analytical capabilities, organizational readiness, and the integration of technology into business processes. In addition, previous studies tend to discuss digital transformation, marketing, and data-driven decision making separately, resulting in limited comprehensive understanding of the relationship among these aspects. Therefore, this study aims to analyze research trends, identify key themes, and reveal research gaps related to digital transformation and data-driven decision making in marketing. This study employed the Systematic Literature Review (SLR) method using the PRISMA approach. A total of 50 selected articles published between 2020 and 2026 from reputable academic databases were analyzed systematically. The findings indicate that digital transformation significantly improves marketing effectiveness, organizational agility, customer engagement, and business performance through the utilization of digital technologies and marketing analytics. However, the successful implementation of data-driven decision making depends not only on technology adoption but also on organizational readiness, leadership support, and human resource capabilities. The study also identified several research gaps, particularly regarding managerial behavior, the balance between data and intuition, and limited empirical studies in SME contexts and developing countries.
Marketing management information system as a sales in-crease strategy in the digital era Endri Susanti; Bonita Misellia; Leonel Hernandez Collante
Information System Analysis, Design and Development Vol. 1 No. 4 (2026): October: Information System Analysis, Design and Development
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/isadd.v1i4.419

Abstract

The digital era has transformed the traditional marketing paradigm into information technology-based marketing that is fast, efficient, and responsive to consumer needs. Marketing Management Information Systems (MIS) are key to strategic marketing decision-making and sales growth in the digital era. This study aims to examine the role of MIS in digital marketing strategies, how digital marketing is implemented to increase sales, and the challenges organizations face in integrating information systems with their marketing strategies. The research method is a literature review of relevant scientific journals and articles in the fields of digital marketing and information management. The results show that proper MIS implementation can improve marketing effectiveness, consumer data optimization, marketing analytics, and digital marketing strategy planning, thereby contributing to increased sales in the digital era.
Information Systems Management in the Era of Intelligent Decision-Making: A Systematic Review of Multi-Criteria Approaches Topan Onassis; Hamdani Hamdani; Herry Ramadhani
Information System Analysis, Design and Development Vol. 1 No. 3 (2026): July: Information System Analysis, Design and Development
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/isadd.v1i3.454

Abstract

Abstract: The development of digital technology in the Industry 4.0 era has driven the transformation of information management towards intelligent decision-making systems. Decision Support Systems (DSS) are important components that help organizations analyze complex data and make optimal decisions. However, increasing data complexity, the integration of intelligent technologies, and the need for multicriteria analysis pose new challenges in the development of such systems. This study aims to systematically examine the development of management information systems in supporting intelligence-based decision-making, with a focus on hybrid models, artificial intelligence-based approaches, and multicriteria decision-making methods. The methods used include a systematic literature review (SLR) following the procedure developed by Kitchenham. This study analyzes the scientific literature on SPK, artificial intelligence, big data analytics, and multicriteria decision-making methods, including AHP, ELECTRE, and fuzzy logic. The results of the study show that integrating artificial intelligence with a multicriteria decision-making method can increase accuracy, flexibility, and the adaptive system's information management capabilities across sectors such as manufacturing, health, and supply chain management. In addition, a hybrid approach that combines data analytics, computational intelligence, and mathematical decision models is more effective in the face of complexity when making modern decisions. Research. This contributes to the development of intelligence based on system information management and provides direction for future research on integrating intelligent technology into decision-making for system support. Keywords: system information management; system supporters decision; artificial intelligence; multicriteria decision making; Industry 4.0; hybrid decision model; big data analytics
Analysis of the Implementation of Electronic-Based Government System (SPBE) in Kutai Kartanegara Regency Muhammad Pandu Utomo Majid; Masjaya; Aulia Rahman Basri; Bonita Misellia; A Suresh Kumar
Information System Analysis, Design and Development Vol. 1 No. 4 (2026): October: Information System Analysis, Design and Development
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study analyzes the implementation of the Electronic-Based Government System (SPBE) in Kutai Kartanegara Regency through a Systematic Literature Review (SLR) approach. The study aims to identify the current condition of SPBE implementation, examine the role of Management Information Systems (MIS) in supporting digital governance and public service effectiveness, compare SPBE implementation in Kutai Kartanegara with best practice regions in Indonesia, identify implementation gaps, and formulate strategic recommendations for optimization. The analysis was conducted using content analysis, comparative analysis, gap analysis, and SWOT analysis based on 20 selected journals related to SPBE, digital governance, and public service digitalization. The findings show that SPBE implementation in Kutai Kartanegara has developed through various digital systems such as village websites, PADU-DESK, E-Kinerja, SIMDA, Command Center, online tax services, and Digital Population Identity (IKD). These systems contributed to improving administrative efficiency, transparency, and public service accessibility. However, several challenges remain, including unequal digital infrastructure, unstable internet connectivity, low digital literacy, limited human resource competence, weak inter-agency integration, and organizational readiness issues. Comparative analysis indicates that regions such as Sumedang, Bandung, Bekasi, and DKI Jakarta demonstrate more integrated and mature SPBE implementation. Meanwhile, Kutai Kartanegara still faces geographical and infrastructure barriers, especially in rural areas. Based on the SWOT analysis, this study recommends strengthening digital infrastructure, improving digital literacy and human resources, enhancing system integration, and developing sustainable digital governance strategies. Overall, SPBE implementation in Kutai Kartanegara shows positive progress but still requires continuous improvement to achieve effective and sustainable digital governance.

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