DIGITAL FORENSIK PADA JARINGAN IOT SMART HOME DENGAN MACHINE LEARNING

ELSI, ZULHIPNI RENO SAPUTRA and Stiawan, Deris and Suprapto, Bhakti Yudho (2025) DIGITAL FORENSIK PADA JARINGAN IOT SMART HOME DENGAN MACHINE LEARNING. Doctoral thesis, Sriwijaya University.

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Abstract

IoT Smart Home (ISH) rentan terhadap berbagai serangan siber, sehingga diperlukan pendekatan digital forensik yang efektif. Penelitian ini mengembangkan model forensik berbasis machine learning untuk mendeteksi serangan dalam jaringan ISH. Proses penelitian meliputi ekstraksi fitur, balancing data SMOTE dan RCS, seleksi fitur Chi-Square, Mutual Information, AND, OR, serta klasifikasi menggunakan beberapa algoritma ML seperti Decision Tree dan Naive Bayes. Dataset MQTT-IoT-IDS2020 digunakan sebagai sumber data utama. Hasil penelitian menunjukkan akurasi tertinggi mencapai 100% pada kombinasi fitur dan algoritma tertentu, serta performa efisien dari sisi waktu pelatihan. Model ini diharapkan dapat mendukung pengembangan sistem forensik dan keamanan IoT yang lebih adaptif dan akurat.

Item Type:	Thesis (Doctoral)
Uncontrolled Keywords:	Digital Forensik, Internet of Things, Smart Home, Feature extraction, Teknik Balancing, Feature Selection.
Subjects:	T Technology > T Technology (General) > T57.6-57.97 Operations research. Systems analysis > T57.85 Network systems theory Including network analysis Cf. TS157.5+ Scheduling T Technology > TA Engineering (General). Civil engineering (General) > TA1-2040 Engineering (General). Civil engineering (General) > TA158.7 Computer network resources Including the Internet T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7885-7895 Computer engineering. Computer hardware Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4150-4380 Computer network resources
Divisions:	03-Faculty of Engineering > 21001-Engineering Science (S3)
Depositing User:	Zulhipni Reno Saputra
Date Deposited:	28 May 2025 03:44
Last Modified:	28 May 2025 03:44
URI:	http://repository.unsri.ac.id/id/eprint/174279

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