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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Inkubis: Jurnal Ekonomi dan Bisnis Jurnal Indonesia Sosial Teknologi
Gunawan Wang
Universitas Bina Nusantara
Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences

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The Artificial Intelligence (AI) Model Canvas Framework and Use Cases Aldian Nurcahyo; Jarot Suroso; Gunawan Wang
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 1 (2022): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i1.22206

Abstract

Artificial Intelligence (AI) has grown increasingly in the past decade. The growth and development bring up several issues for a successful AI project. The AI project requires communication across different domains, like specialists, engineers, data scientists, stakeholders, and ecosystem partners (analytic, storage, labeling, and open-source platforms). It offers numerous vital qualities to give deeper insights into user behavior and give recommendations based on the data. The AI project is hard to define, it requires more than mastery of data, and every enterprise needs guidance and a simple plan on how to use AI. This research creates a wide-view approach of different types of AI Model Canvas for companies that do projects, produce, promote and provide AI technology to organizations. We selected three canvases that represented AI, Machine Learning (ML), and Deep Learning (DL) method. We illustrate and interpret those canvas along with some case studies. We conclude our research by writing the final case report for each use case from the AI model canvas. By filling the one-page Canvas, it will help us explain what AI will provide, how it will interact with humans judgment, and how it will be used to influence decisions, how you will measure success & outcome, and the type of data needed to train, operate, and improve AI. The AI Model Canvas purposed a clear description and differentiation of the roles of stakeholders, customers, and AI strategy. This canvas also can be used in analytical and assembly projects in making new product lines.
eval_uation of IT Governance at Credit Union XYZ Financial Institutions Using COBIT 5 Framework Vinsensius Rekat; Gunawan Wang
Jurnal Indonesia Sosial Teknologi Vol. 5 No. 9 (2024): Jurnal Indonesia Sosial Teknologi
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jist.v5i9.4628

Abstract

Since 2002, Credit Union XYZ has been utilizing information technology in its lending operations. However, the utilization of IT governance has not been optimal due to various weaknesses, obstacles, and issues such as server problems, downtime for maintenance, system change requests, human resources, and recurring IT-related problems. This research aims to assess the current IT governance capabilities at Credit Union XYZ. The method used is the COBIT 5 standard with a focus on the APO and DSS domains tailored to the existing issues. Data were collected through questionnaires distributed to the IT team and relevant stakeholders. The selected COBIT 5 processes include APO06 (Manage budget and costs), APO07 (Manage human resources), DSS01 (Manage operations), DSS02 (Manage service requests and incidents), and DSS03 (Manage problems). The eval_uation reveals a 1 level gap in IT governance capabilities, with the current level at level 2 in Credit Union XYZ, while the target is level 3 in the future. The researcher's recommendation to Credit Union XYZ is to align IT processes with the standards and regulations established by COBIT 5.
Business Process Management of Vehicle Sales and After-Sales Services: A Case Study in an Indonesian Auto Company Billie Enceil; Gunawan Wang
Inkubis : Jurnal Ekonomi dan Bisnis Vol. 8 No. 2 (2026): INKUBIS Jurnal Ekonomi Dan Bisnis
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/inkubis.v8i2.257

Abstract

Background: XYZ, Inc., a medium-sized automotive company specializing in vehicle sales and repair services, faces significant operational challenges arising from manual processes, fragmented information systems, and limited interdepartmental coordination. These inefficiencies result in extended processing times, reduced data accuracy, and a negative impact on customer satisfaction (CSAT). Objective: This study aims to analyze and redesign the vehicle sales and repair service processes at XYZ, Inc. using the Case Study framework. BPMN 2.0 was employed to identify bottlenecks, misalignments among sales, repair, and inventory units, and sources of manual data entry inefficiency. Methods: This research adopts a qualitative descriptive case study design following the five-stage BPM Lifecycle (identification, discovery, analysis, redesign, and implementation). Data were collected through structured interviews, direct observation, and document review. BPMN 2.0 was used to model as-is and to-be processes, and performance gaps were measured by comparing actual versus expected processing times across key activities. Results: The redesigned processes led to faster processing times, a reduction of errors, and improved data sharing among departments. Post-project assessments showed that BPM enhances customer experience by facilitating faster service delivery and response. Additionally, performance analytics were implemented to track top-level metrics such as cycle time, data quality, and repair response time. Conclusion: BPM implementation at XYZ, Inc. resulted in significant reductions in processing time for vehicle sales and repair activities, including a reduction in Sales Order Preparation from 18.5 to 9 hours and Parts Ordering from 8 to 2 hours. The redesigned processes improved data accuracy, interdepartmental integration, and overall operational efficiency. These findings demonstrate the practical value of the BPM Lifecycle approach in the automotive retail and service sector.
Co-Authors Billie Enceil Jarot S. Suroso Vinsensius Rekat