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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer BERNAS: Jurnal Pengabdian Kepada Masyarakat Universitas Muhammadiyah Yogyakarta Undergraduate Conference Proceeding Ramatekno Cendikia: Jurnal Pendidikan dan Pengajaran Jurnal Polimesin NALAR FIQH: Jurnal Hukum Islam Journal of Applied Science and Advanced Engineering
Deni Kurnia
Politeknik Enjinering Indorama
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Mapping IoT Applications in the Textile Industry: A Bibliometric Study using Biblioshiny and VOSviewer Kurnia, Deni; Sutanto, Agus; Fakhrurroja, Hanif; Son, Lovely
Proceedings of Universitas Muhammadiyah Yogyakarta Graduate Conference Vol. 5 No. 2 (2025): Fostering Gen Z for Sustainable Development and Renewable Energy
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/grace.v5i2.677

Abstract

The rapid advancement of technology, particularly the Internet of Things (IoT), has had a transformative impact on various industries, including the textile sector. IoT facilitates real-time data collection, monitoring, analysis, and decision-making, thereby enhancing efficiency, productivity, and resource sustainability. However, a comprehensive bibliometric study of IoT applications in the textile industry has yet to be undertaken. To address this research gap, this study employs bibliometric methods using the Biblioshiny R package and VOSviewer to examine research trends, key contributors, and emerging themes. By analyzing 177 relevant publications from 2015 to 2025, the study identifies major research directions, influential authors, leading institutions, and evolving areas of interest. The findings highlight a growing research focus on IoT-driven textile innovations, particularly the development of electronic textiles (e-textiles), which integrate electronic components into wearable devices for human use. This positioning of e-textiles at the forefront of smart wearable technology underscores their significance as a critical area of exploration within contemporary textile engineering. Furthermore, China, the United States, and India emerge as the predominant contributors to this research domain. The insights derived from this study offer valuable guidance for researchers, industry professionals, and policymakers, supporting future advancements and innovations in IoT applications within the textile industry.
A hybrid pareto–fishbone and IoT-based monitoring framework for reducing DTY yarn defects Kurnia, Deni; Fakhrurroja, Hanif; Marno, Marno; Joniko, Joniko
Jurnal Polimesin Vol 23, No 6 (2025): December
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v23i6.7678

Abstract

Quality Control (QC) challenges in the textile industry increasingly require data-driven and real-time solutions to reduce critical production defects. This research aims to develop a hybrid Pareto-Fishbone analysis integrated with an IoT-based monitoring framework to reduce the incidence of dominant defects in Draw Textured Yarn (DTY) yarns (X-stitch and Broken Filament). Defect data collected in 2024 (n=2,396) and early 2025 (n=1,177) were analyzed using Pareto charts, which identified X-stitch (40.15%) and Broken Filament (37.15%) as contributing 77.3% of total defects in 2024. Fishbone diagrams traced root causes to machine vibration and yarn tension anomalies. An IoT prototype was designed using ADXL345 vibration sensors (200 Hz sampling), tension monitoring, and MQTT communication to a Node-RED dashboard to enable real-time alerts. Preliminary testing achieved 95% MQTT transmission success and detected vibration anomalies correlating with 85% of X-stitch incidents. The proposed hybrid framework combines the diagnostic strength of Pareto–Fishbone analysis with the preventive capability of IoT monitoring, offering a scalable Industry 4.0-oriented solution for textile QC and predictive maintenance.
Co-Authors Adolf Asih Supriyanto Afzeri Afzeri Afzeri Afzeri Tamsir Agus Sutanto Dwi Kartini, Dwi Emmanuel Agung Nugroho Fakhrurroja, Hanif Friska Abadi Habibillah, M. Raihan Hadisantoso, Feri Siswoyo Hakim, Muhammad Nur Imam Muis H Irmani, Irmani Irvan Irvan Itqan Mazdadi, Muhammad Jalil, Lisya Auliyah Joniko, Joniko Kiki Pratiwi Koto, Muthya Khairunnisa Lovely Son, Lovely Marfinas, Zelki Marno Marno Maryani Maryani Nurmala , Indriani Siti Pratama, M. Ridho Radityo Adi Nugroho Sabrina Aisyah Putri Sinaga, M. Hendri Sugara Slamet Riyadi Slamet Riyadi Syahril, Ahmad Syamsiar, Syamsiar Tiawan Wibowo, Nanang Roni Widiawati, Windi