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primary topic: Hydrogen Sulfide Leak Detection Using The C4.5 Algorithm: Optimizing Feature Extraction For Enhanced Accuracy

Hydrogen Sulfide Leak Detection Using The C4.5 Algorithm: Optimizing Feature Extraction For Enhanced Accuracy
type: AcademicArticle
type: Article
abstract: Hydrogen sulfide (H₂S) is a toxic and potentially hazardous gas commonly found in industrial environments, where leaks can lead to serious health and safety risks. Effective detection of H₂S leaks is essential for preventing accidents and ensuring workplace safety. This study explores the implementation of the C4.5 algorithm combined with optimized feature extraction techniques to improve the accuracy of H₂S leak detection. By utilizing feature extraction, significant attributes of gas leak indicators are identified and analyzed, enhancing the classification accuracy of the C4.5 algorithm. The experimental results demonstrate that optimized feature extraction can significantly improve the algorithm’s ability to detect H₂S leaks promptly and accurately. The proposed method not only offers a reliable solution for gas leak detection but also contributes to safer industrial monitoring practices. This study highlights the potential of machine learning techniques, particularly decision tree-based methods, to advance environmental safety through intelligent monitoring systems.
date: 2026-01-01
volume: 1
is part of: PROCEEDING Al Ghazali Internasional Conference The Future is Now: Adaptation to the World’s Emerging Technologies
status: peerReviewed
status: published
author list: authors
creator: Hastuti Dwi Issadari Hastuti
type: EPrint
type: ArticleEPrint
is part of: repository
has document: Hydrogen Sulfide Leak Detection Using The C4.5 Algorithm: Optimizing Feature Extraction For Enhanced Accuracy (Text)
subject: QD Chemistry

Hydrogen Sulfide Leak Detection Using The C4.5 Algorithm: Optimizing Feature Extraction For Enhanced Accuracy (Text)
type: Document
has file: LIT 2024 Desember Mula Agung Barata, Dwi Irnawati, Ifnu Wisma Dwi Prastya, Dwi Issadari Hastuti.pdf
has part: LIT 2024 Desember Mula Agung Barata, Dwi Irnawati, Ifnu Wisma Dwi Prastya, Dwi Issadari Hastuti.pdf

PROCEEDING Al Ghazali Internasional Conference The Future is Now: Adaptation to the World’s Emerging Technologies
type: Organization

PROCEEDING Al Ghazali Internasional Conference The Future is Now: Adaptation to the World’s Emerging Technologies
type: Collection
issn: 30325587

Hastuti Dwi Issadari Hastuti
type: Person
given name: Hastuti
family name: Dwi Issadari Hastuti

Irnawati Dwi Irnawati
type: Person
given name: Irnawati
family name: Dwi Irnawati

Barata Mula Agung Barata
type: Person
given name: Barata
family name: Mula Agung Barata

Universitas Bojonegoro
type: Organization

HTML Summary of #4859 Hydrogen Sulfide Leak Detection Using The C4.5 Algorithm: Optimizing Feature Extraction For Enhanced Accuracy
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primary topic: Hydrogen Sulfide Leak Detection Using The C4.5 Algorithm: Optimizing Feature Extraction For Enhanced Accuracy

QD Chemistry
type: Concept