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Nampira, Ardi Azhar
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Journal : West Science Interdisciplinary Studies

 1 
Bibliometric Analysis of Artificial Intelligence Development in Customer Service Automation Judijanto, Loso; Vandika, Arnes Yuli; Nampira, Ardi Azhar
West Science Interdisciplinary Studies Vol. 3 No. 04 (2025): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v3i04.1861

Abstract

This study presents a comprehensive bibliometric analysis of scholarly literature on the development of artificial intelligence (AI) in customer service automation, based on data extracted from the Scopus database between 2000 and 2024. Using VOSviewer, the analysis maps the intellectual structure, thematic evolution, and collaborative networks within this rapidly growing research field. Findings reveal that core research themes revolve around customer satisfaction, chatbots, natural language processing, and machine learning—highlighting the shift from back-end AI infrastructure toward user-facing, interactive applications. The overlay visualization indicates a temporal progression, with earlier studies focusing on big data and cloud computing, while more recent works emphasize conversational AI and customer experience. Co-authorship and country collaboration networks show two dominant scholarly communities—one centered in East Asia with a technical focus, and another in Western countries emphasizing service quality and marketing perspectives. Despite the field's growth, gaps remain in cross-regional collaboration, ethical design, and theoretical integration. This study offers valuable insights for researchers, practitioners, and policymakers aiming to advance AI-driven customer service strategies that are both innovative and ethically sound.
Impact Analysis of Millennial Financial Literacy and Digital Ecosystem Collaboration on Operational Efficiency and Financial Performance of Start-ups in Jakarta Nampira, Ardi Azhar; Apriyanto, Apriyanto; Arisondha, Edy
West Science Interdisciplinary Studies Vol. 3 No. 05 (2025): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v3i05.1903

Abstract

This study investigates the impact of Millennial Financial Literacy and Digital Ecosystem Collaboration on Operational Efficiency and Financial Performance in Jakarta-based startups. Using quantitative analysis with 180 samples and Structural Equation Modeling - Partial Least Squares (SEM-PLS), the research identifies significant positive relationships among the variables. Millennial Financial Literacy enhances decision-making and resource allocation, driving operational efficiency and financial performance. Digital Ecosystem Collaboration is shown to have the strongest effect on operational efficiency and financial performance, emphasizing its role in fostering innovation and efficiency. The findings highlight operational efficiency as a critical mediator, bridging financial literacy, collaboration, and financial outcomes. Practical implications include fostering financial education and leveraging ecosystem partnerships for startups to achieve holistic growth. These results contribute to the literature on digital entrepreneurship and provide actionable insights for startup managers.
The Effect of Digital Twin and Edge AI on Industrial Machine Maintenance Optimization in Karawang Saleh, Mohamad Zein; Nampira, Ardi Azhar; Iskandar, Yusuf
West Science Interdisciplinary Studies Vol. 3 No. 06 (2025): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v3i06.1988

Abstract

This study investigates the impact of Digital Twin and Edge AI technologies on optimizing industrial machine maintenance in Karawang, Indonesia. Using a quantitative research approach, data were collected from 80 respondents via a Likert-scale questionnaire and analyzed using SPSS version 25. The findings reveal significant positive relationships between both technologies and maintenance optimization. Digital Twin technology enhances predictive maintenance by enabling real-time simulations, while Edge AI improves decision-making through decentralized data processing. Together, they explain 58% of the variance in maintenance optimization. These results emphasize the synergistic effects of these technologies in reducing downtime, improving operational efficiency, and achieving cost savings. This research contributes to the understanding of advanced technological adoption in industrial maintenance and provides practical implications for enhancing productivity in industrial settings.
Bibliometric Review on Infrastructure Monitoring with IoT Judijanto, Loso; Justam, Justam; Nampira, Ardi Azhar
West Science Interdisciplinary Studies Vol. 3 No. 06 (2025): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v3i06.2013

Abstract

The integration of the Internet of Things (IoT) into infrastructure monitoring has transformed how built environments are observed, maintained, and managed. This study conducts a comprehensive bibliometric review to map the research landscape, thematic trends, and collaboration patterns in the domain of IoT-based infrastructure monitoring. Using data retrieved from the Scopus database (2010–2024) and analyzed through VOSviewer, the study identifies key research clusters, influential authors, prolific countries, and the evolution of core topics over time. Results show that the research focus has shifted from basic sensor deployment and data acquisition to advanced topics such as machine learning, edge computing, data privacy, and cybersecurity. India, China, and the United States emerge as leading contributors, with dense global collaboration networks. The study highlights both the maturity of core research areas and the emergence of new directions such as blockchain integration and privacy-preserving infrastructure systems. These findings provide valuable insights for academics, policymakers, and practitioners aiming to enhance infrastructure resilience and efficiency through IoT technologies.
Co-Authors . Syamsulbahri Akhtar, Shazia Al-Momani, Ammar Apriyanto, Apriyanto Arinie, Farida Arisondha, Edy Arnes Yuli Vandika Baso Intang Sappaile, Baso Intang Chai, Som Chairuddin Costa, Bruna Costa, Tiago Devi, Syahrani Diana Suksesiwaty Lubis Dina Destari Edwin Sugesti Nasution Eva Desembrianita Farah, Rina Fernandez, Carlos Fernandez, Carloz Fujita, Miku Gomez, Raul Harja, Ngiw Aman Idris, Haziq Iqbal, Kiran Irwanto, Miko Mei Iwan Harsono JAROT BUDIASTO Jenheri, Jenheri Judijanto, Loso Justam, Justam Kara, Sevda Kaya, Cemil Khan, Omar Lee, Ava Lek, Siri Lim, Sofia Lima, Rafaela Liu Yang M. Yogi Riyantama Isjoni M. Zai, Yovita Yulia Malik, Fatima Manik, Erba Kalo Martinez, Isabel Mayasari, Nanny Mendes, Clara Moktar, Brilian Muhammad Faisal Ninik Sri Rahayu, Ninik Sri Noor, Asmirin Nurjannah Nurjannah Nurul Huda Pangastuti, Nova Pong, Ming Putri, Agustin Andhika Rahman, Alkautsar Ramos, Nathaniel Razak, Faisal Rejeki, Marsudi Endang Sri Restu Auliani Reyes, Maria Clara Rudy Haryanto Saleh, Mohamad Zein Samaduri, Lutpi Santos, Luis Sari, Arum Fandan Sari, Ira Wulan Sato, Haruka setiawati, rahmi Setyowati Subroto Sinaga, Jernita Siti Aisyah Hanim, Siti Aisyah Siti Annisa Wahdiniawati, Siti Annisa Siti Shofiah Sothy, Chak Souza, Felipe Sulaiman Sulaiman Tahir, Usman Tan, Marcus Taryana Taryana, Taryana Taufik Taufik Telma Anis Safitri Urnika Mudhifatul Jannah, Urnika Mudhifatul Vita Lystianingrum Wiwit Xiang, Yang Yuliana, Ana Yusuf Iskandar Zahir, Roya Zaman, Khalil Zhang Li