Article Per Year (5 Year)
p-Index From 2021 - 2026
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This Author published in this journals
All Journal Journal of English in Academic and Professional Communication Journal of Embedded Systems, Security and Intelligent Systems
Ade Irawan
Politeknik Negeri Samarinda
Computer Science & IT Languange, Linguistic, Communication & Media

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Fire Detection and Room Firefighting System Based on IoT Using C4.5 Decision Tree Algorithm Rika Ismayanti; Fara Triadi; Arsan Kumala Jaya; Ade Irawan
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 4 (2025): Desember 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i4.10685

Abstract

Early fire detection is a critical requirement in indoor safety systems, where delays of only a few seconds can escalate into severe damage and casualties. Conventional devices often rely on single-sensor thresholds, which are highly susceptible to false alarms and unstable performance in dynamic indoor environments. This study develops an Internet of Things (IoT)-based multi-sensor fire detection and autonomous firefighting system integrated with a C4.5 decision tree classifier for real-time hazard recognition and short-term risk prediction. The prototype combines DHT22 temperature, MQ-135 gas, infrared flame, and ultrasonic water-level sensors with an ESP32 microcontroller, servo-controlled nozzle, and pump-based water spraying, all connected to an Android–Firebase platform for remote monitoring. A multivariate time-series dataset of 200 sensor sequences was preprocessed using a five-step sliding-window model and evaluated through 1,000 repeated hold-out trials. The C4.5 classifier achieved a mean accuracy of 84.9%, with peak values exceeding 90%, and clearly separated Safe, Alert, and Danger states, with smoke concentration emerging as the dominant predictor. Experimental tests in a 60 × 40 × 30 cm chamber produced 1–2 s reaction times, eight successful extinguishing events, and four failures attributable to mechanical belt detachment rather than model errors. These findings indicate that interpretable decision-tree models, when combined with IoT sensing and autonomous actuation, can provide a low-cost framework for real-time fire warning and automatic suppression. Future work should address mechanical robustness, extended deployment, and multi-room scalability
Exploring Students’ Participation in English Classrooms in Higher Education Dwi Titi Maesaroh; Ade Irawan
Journal of English in Academic and Professional Communication Vol 12 No 2 (2026): July (in Progress)
Publisher : Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/jeapco.v12i2.6224

Abstract

Students’ class participation is essential in English learning, as it facilitates improvement in language proficiency. This study aims to explore how students self-assess their class participation and to ascertain the key determinants that deter students’ active engagement in classroom activities at the higher education level. This study employed a mixed-method research design to investigate university students’ perceptions and self-assessments of their participation in English language classrooms, involving 22 respondents within a single classroom setting. Data was collected through closed-ended and open-ended questionnaires.  The results highlight notable barriers to in-class participation, including personal issues such as transportation to class, anxiety about asking or responding to questions, and limited English proficiency.  The results also show how crucial a supportive environment, well-prepared lectures, and group discussions during learning are for encouraging participation. This study sheds light on how students engage in class and what motivates them to be active or passive participants, both for English teachers and lecturers.
Co-Authors Arsan Kumala Jaya Dwi Titi Maesaroh Fara Triadi Rika Ismayanti