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All Journal Jiko (Jurnal Informatika dan komputer) International Journal of Economics, Business and Accounting Research (IJEBAR) Jurnal Tekinkom (Teknik Informasi dan Komputer) Budimas : Jurnal Pengabdian Masyarakat International Journal of Computer and Information System (IJCIS) Proceeding of The International Conference on Electrical Engineering and Informatics
Muqorobin Muqorobin
ITB AAS Indonesia
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Social Sciences Other

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Design and Implementation of a Cloud- and AI-Based Framework for Managing the Assessment Cycle and Talent Development in the Electric Vehicle Industry Muqorobin Muqorobin; Sumadi Sumadi; Tira Nur Fitria
International Journal of Computer and Information System (IJCIS) Vol 6, No 4 (2025): IJCIS : Vol 6 - Issue 4 - 2025
Publisher : Institut Teknologi Bisnis AAS Indonesia

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

Abstract

The rapid growth of the electric vehicle (EV) industry creates an urgent need for scalable, data-driven talent management systems capable of aligning workforce competencies with evolving technological demands. This study proposes and implements a cloud- and artificial intelligence (AI)-based framework for managing the full assessment cycle and talent development processes in EV-related organizations. The framework integrates psychometric and technical assessments, competency profiling, learning path recommendations, and performance analytics into a unified digital platform. Using a design-science approach, the research specifies requirements with industry stakeholders, designs an end-to-end system architecture, and evaluates its feasibility and perceived usefulness through expert review and pilot deployment. Initial findings indicate that the framework enhances visibility of talent pipelines, supports more objective and continuous assessment, and enables personalized upskilling strategies that are better aligned with EV industry competency standards. The proposed framework offers a replicable model for other advanced manufacturing and green technology sectors seeking to accelerate workforce readiness through cloud-native and AI-enabled solutions.
Management Information System Based on IoT and Big Data Technology for Optimization of Supply Chain Muqorobin Muqorobin; Farid Fitriyadi
International Journal of Computer and Information System (IJCIS) Vol 6, No 4 (2025): IJCIS : Vol 6 - Issue 4 - 2025
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v6i4.261

Abstract

This paper explores the integration of Internet of Things (IoT) and Big Data Analytics for optimizing supply chain management. With increasing complexity in global supply chains, traditional information systems fall short in providing real-time visibility, accurate forecasting, and agile decision-making. IoT technology facilitates real-time data collection through sensors embedded in goods, vehicles, and production systems, while Big Data analytics processes these high-volume, real-time data streams to generate actionable insights. By integrating these technologies into a Management Information System (MIS), this paper proposes a framework that enhances supply chain visibility, forecasting accuracy, and responsiveness. The study examines how IoT-enabled sensors and big data analytics improve logistics, inventory management, and risk mitigation. Key challenges, including data security, interoperability, and infrastructure costs, are also addressed. The proposed MIS architecture offers a foundation for building smart, adaptive, and resilient supply chains, transforming decision-making from reactive to proactive. The findings suggest significant improvements in operational efficiency and supply chain agility. This paper concludes with implications for practitioners and calls for further empirical research to validate the proposed system in real-world settings.
Designing an E-Commerce Website to Enhance the Purchasing Power of SMEs Based on Augmented Reality (AR) Muqorobin Muqorobin; Sumadi Sumadi; Tira Nur Fitria
International Journal of Computer and Information System (IJCIS) Vol 6, No 3 (2025): IJCIS : Vol 6 - Issue 3 - 2025
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v6i3.248

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play an important role in economic growth; however, they still face challenges in increasing consumers’ purchasing power in the digital era. This study aims to design an Augmented Reality (AR)-based e-commerce website to enhance the purchasing power of MSME products. AR technology allows consumers to visualize and interact with products virtually, providing a more engaging, informative, and realistic shopping experience. The research methodology includes user needs analysis, system design, and the development of an e-commerce website integrated with AR features. The results indicate that the implementation of AR in e-commerce websites can increase consumer trust and purchase intention toward MSME products. Through more detailed and interactive product visualization, consumers are able to make purchasing decisions with greater confidence. Therefore, an AR-based e-commerce website is expected to serve as an innovative solution to improve the competitiveness and purchasing power of MSME products in the digital market.
Data-Driven Sustainability in Culinary SMEs: Integrating Green HRM, Decision Support, Halal Traceability, and Green Operations Indah Wahyu Utami; Muqorobin Muqorobin; Erna Indriastiningsih
International Journal of Computer and Information System (IJCIS) Vol 6, No 4 (2025): IJCIS : Vol 6 - Issue 4 - 2025
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v6i4.303

Abstract

Culinary small and medium-sized enterprises (SMEs) operate at the intersection of volatile demand, perishable inventories, labor-intensive processes, food-safety and halal-integrity requirements, and growing pressure to reduce waste and improve sustainability. Yet the relevant management literature remains fragmented. Digital transformation studies emphasize technology adoption and decision quality; Green Human Resource Management (Green HRM) research emphasizes employee capabilities and green behavior; food-service studies focus on waste prevention and forecasting; halal supply-chain studies focus on integrity and traceability; and supplier-selection research develops multi-criteria tools with limited integration into day-to-day SME decision cycles. This structured integrative review synthesizes recent peer-reviewed research published during 2022–2025 to develop a cross-functional framework for data-driven sustainability in culinary SMEs. Guided by recent good-practice recommendations for management reviews, the paper integrates evidence across digitalization, Green HRM, green operations, food-waste prevention, halal traceability, sustainable supplier selection, dynamic capabilities, and sustainable business performance. The resulting framework conceptualizes three antecedent capabilities—Green HRM capability, digital decision-support capability, and halal supply-chain integrity capability—that converge into a closed-loop green operational capability. This operational capability links sensing, decision, implementation, measurement, learning, and reconfiguration, thereby generating economic, environmental, human-organizational, and supply-chain integrity outcomes. Eight research propositions specify direct, mediated, and complementary relationships among the constructs. The paper contributes by shifting the debate from isolated green or digital practices toward an integrated decision architecture suitable for resource-constrained culinary SMEs. It also provides a research agenda for empirical validation and a design logic for future smart-green-halal decision-support systems without presuming that a particular technology has already been validated..
Design and Functional Validation of an AI-Enabled Social Accounting and Performance Excellence Decision-Support System for Dental Clinic Networks Mahameru Rosy Rochmatullah; Muqorobin Muqorobin; Didik Prasetyanto; Dewi Setyoningsih
International Journal of Computer and Information System (IJCIS) Vol 6, No 4 (2025): IJCIS : Vol 6 - Issue 4 - 2025
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v6i4.306

Abstract

Multi-unit dental service organizations require integrated monitoring of organizational performance, service quality, patient experience, and social impact. Conventional dashboards usually report historical indicators but provide limited support for linking performance deviations to traceable managerial action. Objective: This study aimed to design, develop, and functionally validate an artificial-intelligence (AI)-enabled decision-support system integrating Social Accounting and Performance Excellence principles for dental clinic networks. Methods: A Design Science Research approach guided problem identification, requirements analysis, artifact design, prototype development, demonstration, and functional evaluation. The prototype integrates organizational KPIs, social-impact indicators, branch comparison, SOP/audit functionality, role-based processes, SQLite persistence, and AI-supported managerial insights. In addition to the documented local functional test, a reproducible synthetic engineering dataset comprising 30 branch-month records (five fictional branches over six months) was generated to verify KPI calculations, social-impact aggregation, prioritization, and anomaly-oriented decision logic when real operational data were unavailable. The synthetic observations contain no real patient or clinic records and are not treated as UAT evidence. Results: The study produced an executable Alpha v0.1 prototype that runs on localhost and supports indicator input, data persistence, KPI summarization, analytical insight generation, branch-level comparison, and audit-oriented workflow. The available technical evidence reports 10 of 10 predefined local functional checks as PASS (100%). In the supplementary synthetic verification, the 30 records yielded a network mean performance index of 85.2, mean social-impact index of 80.5, and mean combined score of 83.3. The deliberately stressed fictional branch B04 was classified as high priority in all six simulated months, whereas B02 produced the highest mean combined score (90.4), demonstrating the expected discrimination of the analytical rules. Conclusion: The artifact demonstrates the technical feasibility of integrating Social Accounting, Performance Excellence, and AI-supported organizational analytics in a unified dental-network decision-support system. The synthetic exercise strengthens engineering verification of the analytical logic but does not substitute for relevant-environment user validation, real-data validation, or clinical evaluation.
Co-Authors Agus Prasetya Amelia Shinta Dewi Annisaa Miftakhul Jannah Ardhan Sindu Prakoso Ayu Sri Muryani Bramasto Wiryawan Yudanto Dewi Setyoningsih Didik Prasetyanto Dziky Ridhwanullah Dziky Ridwanullah Fatkhurrochman, Fatkhurrochman Fidi Febriani Fitria, Tira Nur Fitriyadi, Farid Hadi Samanto Ihsan Cahyo Utomo Iin Emy Prastiwi Indah Wahyu Utami Indriastiningsih, Erna Itsney Nur Hikmah Kusrini Laidestifre Putri Santoso LMS. Kristiyanti M Hasan Ma'ruf M. Hasan Ma'ruf Mahameru Rosy Rochmatullah Moch. Bagoes Pakarti, Moch. Bagoes Muslihah, Isnawati Nendy Akbar Rozaq Rais Nendy Akbar Rozaq Rais Nur Fatihatul Jannah Rahmawati Rahmawati Resa Dwi Tristanto Rita Noviani Rohmah Tulaila Rukmini Rukmini Sarah Rum Handayani Siti Arifah Siti Nurlaela Siti Nurlaela Siti Rokhmah Siti Rokhmah Siti Rokhmah Siti Rokhmah Siti Rokhmah Sri Laksmi Pardanawati Sri Mulyani Sumadi Sumadi Suprihati Syaifudin Fendi Prasetyo Tino Feri Efendi Tino Feri Effendi Umar Chamdani Nur Widiyanto, Wahyu Wijaya Yusuf Wahyu Setiya Putra Yuwita Ariessa Pravasanti