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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Kreativitas PKM
Daniel Ngolu Jiledo Maringga
Universitas Negeri Yogyakarta
Computer Science & IT Electrical & Electronics Engineering Health Professions Medicine & Pharmacology Nursing Public Health

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Success Factors in the Implementation of IoT-Enabled Predictive Maintenance Technology in Industrial Electrical Applications: A Systematic Literature Review Daniel Ngolu Jiledo Maringga; Muhamad Ali; Ridho Azahar
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 12 No. 1 (2026): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v12i1.31651

Abstract

The development of the Internet of Things (IoT) in predictive maintenance (IoT-enabled Predictive Maintenance) for industrial electrical equipment offers significant potential to enhance system efficiency and reliability; however, its implementation is constrained by challenges related to sensor data integration, communication infrastructure quality, and security issues. This study addresses a gap in the literature by describing patterns of successful IoT-enabled Predictive Maintenance implementation in industrial electrical applications. The contribution of this research lies in providing a systematic synthesis of leading technologies and key success factors in the adoption of IoT-enabled Predictive Maintenance.  The method employed is a Systematic Literature Review (SLR) using the PRISMA approach, which resulted in 16 relevant articles. The findings indicate that the combination of IoT technologies, sensors, wireless networks, and edge-cloud architecture represents an appropriate technological configuration for building an effective Predictive Maintenance chain. These implementations are predominantly found in the manufacturing, energy, and transportation sectors, with the main success factors determined by data quality and network sustainability. These findings offer practical solutions for industry practitioners in improving the efficiency and sustainability of their systems. In conclusion, the successful implementation of IoT-enabled Predictive Maintenance in industrial electrical systems is highly dependent on the suitability of technological infrastructure, data governance, and service-based business models, while also opening opportunities for further research and the expansion of applications into other sectors.
Enhancing Energy-Efficient Building Literacy Through Education and School Environment Identification Among Vocational High School Students Sarwa Sarwa; V. Lilik Hariyanto; Ridho Azahar; Daniel Ngolu Jiledo Maringga
Jurnal Kreativitas Pengabdian Kepada Masyarakat (PKM) Vol 9, No 9 (2026): Volume 9 Nomor 9 (2026)
Publisher : Universitas Malahayati Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33024/jkpm.v9i9.27371

Abstract

ABSTRACT The building sector contributes significantly to energy consumption; therefore, literacy regarding energy-efficient buildings needs to be strengthened from the school education stage onwards. This study aims to analyse improvements in understanding and the ability to identify energy-efficient buildings within the school environment. The study employed an educational-participatory approach with a single-group pre-test–post-test design. The research sample consisted of 30 Year 10 students from the Construction and Housing Technology Department at SMK Negeri 1 Percut Sei Tuan. The activities were carried out over four sessions, comprising the delivery of material, discussions, a pre-test, a post-test, and practical exercises in identifying aspects of natural lighting, ventilation, lighting usage, and user behaviour. Data were analysed using descriptive statistics and a paired-samples t-test. The results showed that the mean score increased from 46.80 to 80.43, with the pass rate rising from 0% to 86.67%. Meanwhile, the practical assessment achieved a mean score of 81.90 with a 100% pass rate. The paired-samples t-test revealed a significant difference (p 0.001) between initial and final knowledge. The research findings indicate that education based on direct observation is effective in improving students’ literacy and practical skills regarding the knowledge and identification of energy-efficient buildings. Keywords: Energy-Efficient Buildings, Vocational Education, Participatory Learning, The School Environment.
Co-Authors Muhamad Ali Ridho Azahar Sarwa, Sarwa V. Lilik Hariyanto