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All Journal Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Informatika Global Jurnal Informasi dan Teknologi
Nugraha, Zahra Sabila
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Perancangan Knowledge Management System Resep Masakan Indonesia Menggunakan Model SECI Nugraha, Zahra Sabila; Wibowo, Ishma Tsabita; Maulana Asykari Muhammad; Yuni Sugiarti
Jurnal Ilmiah Informatika Global Vol. 15 No. 3: Desember 2024
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jiig.v15i3.4885

Abstract

Indonesia is rich in diverse traditional culinary heritage, with recipes often passed down orally or as tacit knowledge, making it challenging to preserve and at risk of being lost. This study aims to design a knowledge management system (KMS) for managing, storing, and distributing Indonesian culinary recipes using the SECI model (Socialization, Externalization, Combination, and Internalization). The SECI model was selected for its ability to convert tacit knowledge into explicit knowledge that can be managed and disseminated through information systems. The research method includes needs analysis through literature review, observation, and interviews with culinary community members, along with a design review to understand the characteristics of traditional recipes. The system was developed using JavaScript and the Next.js framework to create a responsive user interface. Testing was conducted using the black-box method to evaluate system performance based on user needs. The results show that the KMS was well-received by users and effectively provided a platform for storing and distributing traditional recipes. This system serves not only as a repository but also as a digital ecosystem supporting the preservation of Indonesian culinary heritage. It is expected that the KMS will be a valuable tool in documenting and disseminating Indonesian culinary knowledge to the wider public, including younger generations and the international community. Further testing is needed to optimize the system for more effective support in preserving Indonesia’s culinary culture.
Analyzing Frameworks for Green IT Adoption in Organizations: A Systematic Literature Review Muhammad, Maulana; Waspodo, Bayu; Nugraha, Zahra Sabila
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.637

Abstract

Sustainability has emerged as a fundamental objective for organizations aiming to achieve the highest levels of maturity within various IT Governance Frameworks. Green IT has emerged as a concept aligned with the essence of organizational sustainability. Its primary challenge lies in the difficulty of integrating Green IT principles into the organization's business processes. Therefore, the framework employed plays a crucial role in facilitating the adoption of Green IT. This Systematic Literature Review uses Kitchenham to review various literature on the topic of Green IT adoption in organizations with a focus on their role in supporting sustainable behaviors. The review process shows the three primary frameworks, namely the Governance and Management Framework for Green IT (GMGIT), the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), and the Green IT Maturity Model. The analysis indicates that these frameworks are primarily employed in the IT services and manufacturing sectors, highlighting their effectiveness in addressing environmental sustainability, carbon emissions, and energy consumption. Gaps remain, especially in the government sector, where Green IT principles are underexplored. The research identifies challenges in executing these frameworks, specifically the tendency to favor short-term adoption strategies over long-term sustainability objectives. To enhance the success of Green IT adoption, firms at maturity levels 1-3 must initially evaluate their preparedness prior to fully integrating Green IT principles into their business processes. This study provides comprehensive insights into the frameworks utilized for Green IT adoption, including substantial recommendations for future research and practical applications in emerging domains.
The Use of Artificial Intelligence in Enhancing Customer Relationship Management (CRM): A Systematic Literature Review Nugraha, Zahra Sabila; Muhammad, Maulana Asykari; Waspodo, Bayu
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 4 (2025): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v14i4.2454

Abstract

Customer Relationship Management (CRM) has become a key business strategy for retaining customers. As data continues to grow in variety and volume, more advanced solutions are needed. The integration of Artificial Intelligence (AI), CRM, and Big Data offers promising support in addressing modern business challenges in the era of digitalization. This study explores the application of Artificial Intelligence in Customer Relationship Management (AI-CRM) through a literature review. We adopted the Kitchenham and Charters method for conducting the review and initially identified 356 studies. Data were collected from 33 studies published in the Scopus, ScienceDirect, and IEEE databases between 2020 and 2025. The results show that supervised learning remains the most widely used AI technique, while deep learning has grown significantly in recent years, indicating a shift toward more sophisticated CRM solutions. Most applications were found in Analytical CRM, particularly for churn prediction, customer segmentation, and personalization. However, challenges related to data quality, bias, privacy, and transparency remain prevalent. Additionally, areas such as B2B and Strategic CRM remain underexplored. This review emphasizes the need for organizational readiness before adopting AI-CRM and highlights AI’s transformative potential to enhance CRM strategies and gain a competitive advantage. The findings deliver useful insights into the application of AI in data-driven CRM.
Co-Authors Bayu Waspodo Maulana Asykari Muhammad Maulana Muhammad, Maulana Muhammad, Maulana Asykari Wibowo, Ishma Tsabita Yuni Sugiarti