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All Journal Journal of Fuzzy Systems and Control (JFSC) Kolaborasi: Jurnal Hasil Kegiatan Kolaborasi Pengabdian Masyarakat
Rio Subandi
Sekolah Tinggi Teknik Pati
Agriculture, Biological Sciences & Forestry Humanities Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Law, Crime, Criminology & Criminal Justice Social Sciences

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Comparative Analysis of Random Forest and LSTM for Predictive Maintenance of Electric Motors Muhammad ‘Atiq; Musab Ali El Nefati; Arief Marwanto; Fajar Husain Asy'ari; Rio Subandi; Danang Hendrawan
Journal of Fuzzy Systems and Control Vol. 4 No. 2 (2026): Vol. 4 No. 2 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i2.421

Abstract

This study presents a comparative analysis of Random Forest and Long Short-Term Memory (LSTM) algorithms for predictive maintenance of electric motors using Industrial Internet of Things (IIoT) sensor data (current, temperature, vibration). A synthetic dataset from Kaggle comprising 5,000 samples across three operational states (HEALTHY, WARNING, CRITICAL) was employed. Experiments were conducted on Google Colab with a Tesla T4 GPU. The LSTM model achieved a classification accuracy of 98.9%, outperforming Random Forest (98.5%), with perfect precision and recall for the WARNING state and improved recall for the CRITICAL state (0.97 vs. 0.96). However, Random Forest demonstrated substantially shorter training time (2 seconds vs. 30 seconds). For real-time industrial deployment on Programmable Logic Controllers (PLCs), Random Forest is recommended due to its rapid inference (5-10 ms), while LSTM is better suited for critical assets where detection accuracy is prioritized. The findings also confirm the viability of Google Colab as an accessible platform for predictive maintenance research in academic settings. This work contributes a practical framework for selecting between machine learning and deep learning approaches in IIoT-based motor fault diagnosis.
Pelatihan Penguasaan Alat Digital untuk Pengajaran Bahasa Inggris Fajar Husain Asy'ari; Zainal Abidin; Bijanto Bijanto; Ellen Proborini; Ainin Maftukhah; Rio Subandi
Kolaborasi : Jurnal Hasil Kegiatan Kolaborasi Pengabdian Masyarakat Vol. 4 No. 3 (2026): September: Kolaborasi : Jurnal Hasil Kegiatan Kolaborasi Pengabdian
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/kolaborasi.v4i3.1055

Abstract

The rapid advancement of digital technology demands that educators integrate technology into the learning process. However, many English teachers still lack adequate competency in utilizing digital tools optimally for teaching. This community service activity aims to enhance English teachers' competence in mastering and implementing digital tools for English language teaching. The training was conducted at STT Pati (Jl. Pati-Trangkil KM 4.5 Ngepungrojo, Trangkil, Pati, Central Java) on January 3, 2026, with 60 English teachers as participants, organized by LP Maarif NU Pati in association with MEC Pati (Maarif English Community) in collaboration with STT Pati. The method used a participatory training approach consisting of five stages: pre-test and needs identification, material presentation, practical exploration, intensive mentoring, and evaluation. The results showed a significant increase in teachers' understanding and skills, with the average pre-test score of 56.8 increasing to 84.5 in the post-test, a 27.7 point improvement. Participants successfully developed innovative English teaching materials using various digital tools such as interactive learning platforms (Quizizz, Kahoot!), multimedia creation tools (Canva, Genially), and online assessment applications (Google Forms). The discussion highlights that a systematic, practice-based training approach with continuous mentoring is effective in improving teacher competence and supporting digital transformation in English language education. Social changes emerged include behavioral changes, formation of a community of practice through MEC Pati, emergence of local leaders, and growing awareness of the importance of technology adaptation. This activity contributes to the development of more engaging, interactive, and effective English learning experiences. The implications emphasize the need for sustainable follow-up programs and institutional support to ensure optimal implementation of digital tools in English teaching.
Co-Authors Ainin Maftukhah Arief Marwanto Bijanto Bijanto Danang Hendrawan Ellen Proborini Fajar Husain Asy'ari Muhammad ‘Atiq Musab Ali El Nefati Zainal Abidin