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Enhancing Intrusion Detection Systems by Integrating Support Vector Machine and Random Forest Classifiers Using Dempster-Shafer Theory

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Published in:Inform: Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi
Format: Online Article RSS Article
Published: 2026
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container_title Inform: Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi
description
discipline_display Computer Engiineering
discipline_facet Computer Engiineering
format Online Article
RSS Article
genre Journal Article
id rss_article:78906
institution FRELIP
journal_source_facet Inform: Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Enhancing Intrusion Detection Systems by Integrating Support Vector Machine and Random Forest Classifiers Using Dempster-Shafer Theory
Computer Engiineering
General
Computer Engiineering
sub_discipline_display General
sub_discipline_facet General
subject_display Computer Engiineering
General
Computer Engiineering
Computer Engiineering
General
Computer Engiineering
subject_facet Computer Engiineering
General
Computer Engiineering
title Enhancing Intrusion Detection Systems by Integrating Support Vector Machine and Random Forest Classifiers Using Dempster-Shafer Theory
title_auth Enhancing Intrusion Detection Systems by Integrating Support Vector Machine and Random Forest Classifiers Using Dempster-Shafer Theory
title_full Enhancing Intrusion Detection Systems by Integrating Support Vector Machine and Random Forest Classifiers Using Dempster-Shafer Theory
title_fullStr Enhancing Intrusion Detection Systems by Integrating Support Vector Machine and Random Forest Classifiers Using Dempster-Shafer Theory
title_full_unstemmed Enhancing Intrusion Detection Systems by Integrating Support Vector Machine and Random Forest Classifiers Using Dempster-Shafer Theory
title_short Enhancing Intrusion Detection Systems by Integrating Support Vector Machine and Random Forest Classifiers Using Dempster-Shafer Theory
title_sort enhancing intrusion detection systems by integrating support vector machine and random forest classifiers using dempster-shafer theory
topic Computer Engiineering
General
Computer Engiineering
url https://ejournal.unitomo.ac.id/index.php/inform/article/view/11075