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All Journal JOCHAC International Journal of Cyber Engineering (IJCE)
Prasetyo Mimboro
Universitas Siber Muhammadiyah
Computer Science & IT

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Identifikasi Penyakit Tanaman Jagung berdasarkan Citra Daun Menggunakan Hybrid k-NN - CNN Prasetyo Mimboro
Journal of Cyber Health and Computer Vol 1 No 1 (2023): Journal of Cyber Health and Computer (JOCHAC)
Publisher : SIBER PRESS Universitas SIBERMU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64163/jochac.v1i1.2

Abstract

Terdapat beberapa penyakit yang dapat menyerang daun pada tanaman jagung seperti northern corn leaf blight, sourthern corn leaf blight, common rust, southern rust, gray leaf spot. Untuk dapat mengantisipasi penyakit tersebut, harus dilakukan upaya dalam mendiagnosa penyakit pada tanaman jagung dengan segera agar penyakit tidak menyebar ke seluruh wilayah pertanian jagung. Penelitian ini bertujuan untuk mengidentifikasi penyakit pada daun jagung berdasarkan citra digital dari daun jagung dengan mengimplementasi algoritme hibrida k-NN - CNN. Pada penelitian ini akan diketahui tingkat akurasi dari metode tersebut untuk membandingkan persentase algoritma hibrida terhadap algoritma machine learning lainnya. Dataset yang digunakan pada penelitian ini berjumlah 5200 data yang terdiri dari 4000 data training dan 1200 data testing. Hasil dari penelitian ini memperoleh tingkat akurasi rata-rata 96,16 % dan persentase error rata-rata sebesar 3, 83%.
Analysis of Async RAT Malware Infection through Network Communication Using Wireshark Prasetyo Mimboro; Mochammad Luthfi Rahmadi; Ashish Jaisan
International Journal of Cyber Engineering Jil. 1 No. 1 (2025): International Journal of Cyber Engineering - December Edition
Publisher : PT Baramedia Literasi Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.68404/ijce.v1i1.10

Abstract

This study investigates the infection process of the Async Remote Access Trojan (Async RAT) and demonstrates how its malicious activity can be identified through network traffic analysis using Wireshark. Async RAT is a remote access malware that enables adversaries to gain complete control over compromised systems. The case study utilizes PCAP files and infection artifacts obtained from malware-traffic-analysis.net to reconstruct the infection chain, beginning with the execution of a suspicious ISO file containing a WSF script and culminating in the malware’s communication with Command and Control (C2) servers. The findings reveal that Async RAT employs both HTTP and HTTPS protocols to retrieve payloads and maintain interaction with remote servers. Furthermore, Indicators of Compromise (IoCs)—including domains, IP addresses, and file hashes—were identified and validated to provide insight into the attack vector. This research contributes to the broader understanding of malware infection patterns and supports the development of effective detection and mitigation strategies in cybersecurity practice.
Co-Authors Ashish Jaisan Mochammad Luthfi Rahmadi