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Intrusion Detection System (Ids) Menggunakan Raspberry Pi 4 dengan Snort Studi Kasus : Laboratorium Jaringan Komputer Politeknik Negeri Bengkalis wahyat, Wahyat; Ryci Rahmatil Fiska; Dedi Hermawan
ABEC Indonesia Vol. 11 (2023): 11th Applied Business and Engineering Conference
Publisher : Politeknik Negeri Bengkalis

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Abstract

Server security on a computer network is very important, maintaining computer network security in order to maintain information, data and maintain infrastructure so that it can work and function properly and provide access rights to registered users, this study aims to build an Intrusion Detection System (IDS) on networks and servers using Raspberry Pi 4 with SNORT which is useful for monitoring Server activities when an attempted attack occurs by sending notifications to BOT Telegram via the administrator's cellphone in realtime, this system is tested with three attack scenarios namely, PING Attack, Port Scanning, and DOS / DDoS Attack. From the results of testing attacks, Snort can detect and provide alerts that will be stored in the Snort Log and forwarded to the Telegram BOT notification in real time.   Keywords: Raspberry pi, Server, IDS, Snort, Bot Telegram
Implementation of Intrusion Detection System With Suricata on Ubuntu 22.04 LTS Wahyat, Wahyat; Kudadiri, Parlindungan
Jurnal Teknologi Elekterika Vol. 21 No. 1 (2024)
Publisher : Jurusan Teknik Elektro Politeknik Negeri Ujung Pandang

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Abstract

This study seeks to put into action and assess the effectiveness of a Suricata based Intrusion Detection System (IDS), on a Linux Ubuntu 22 04 operating system setup. Suricata was selected as the IDS for its features and strong performance, in identifying types of cyber threats. The execution procedure involves setting up Suricata through installation configuring it and conducting tests in a controlled setting. The efficiency assessment entails studying the detection accuracy alarm rate and response time of Suricata when confronted with attack scenarios. The findings, from the research are anticipated to enhance the protection of information systems that operate using Linux as their base platform.
Machine Learning-Based Intrusion Detection System (IDS) for Classifying Types of Attacks on Computer Networks Fiska, Ryci Rahmatil; Wahyat, Wahyat; Hermawan, Dedi; Laurenz, Via; Fateha, Izatul
ABEC Indonesia Vol. 12 (2024): 12th Applied Business and Engineering Conference
Publisher : Politeknik Negeri Bengkalis

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Abstract

Server security on a computer network is very important, maintaining the security of a computer network inorder to maintain information, data and maintain infrastructure so that it can work and function properly and provideaccess rights to registered users, this research, aims to build an IDS (Intrusion Detection System) on the network andServer using Raspberry Pi with SNORT which is useful for monitoring Server activity when an attempted attack occurs.With the increasing complexity of network attacks carried out by attackers, intelligent and adaptive approaches areneeded to detect and overcome these threats. Traditional methods such as rule-based or signatures are often not effectiveenough in the face of evolving attacks. The large amount of network traffic data makes it difficult to manually analyzeand detect attacks. Naive Bayes has a very important role in the classification and detection of network attacks, bothconsidered malicious and highly malicious, By using Naive Bayes, network security systems can become more proactiveand adaptive to attacks. This technology not only helps in detecting familiar attacks but also enables identification andresponse to new or unknown attack techniques. Through proper classification, the system can provide better protectionand reduce the impact of attacks.
Sistem Distribusi Pengairan dan Monitoring Kelembapan Tanah pada Tanaman Cabai Menggunakan Teknologi Internet of Things Supria, Supria; Wahyat, Wahyat; Musri, Tengku
Techno.Com Vol. 24 No. 2 (2025): Mei 2025
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v24i2.12420

Abstract

Penggunaan teknologi Internet of Things (IoT) dalam sistem pertanian modern dapat meningkatkan efisiensi dan efektivitas pengelolaan air, terutama dalam budidaya tanaman cabai yang membutuhkan kelembapan tanah optimal. Sistem pengairan tetes yang dikombinasikan dengan monitoring kelembapan tanah berbasis IoT memungkinkan otomatisasi pengairan berdasarkan kondisi real-time dari tanah, sehingga mengurangi pemborosan air serta menjaga produktivitas tanaman. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem distribusi pengairan tetes otomatis serta monitoring kelembapan tanah pada tanaman cabai dengan memanfaatkan sensor kelembapan tanah yang diintegrasikan dengan platform IoT untuk kontrol dan pemantauan jarak jauh. Hasil pengujian menunjukkan bahwa sistem mampu mengatur irigasi secara otomatis berdasarkan data kelembapan tanah, yang diukur dalam waktu nyata melalui sensor dan dikirimkan ke pengguna melalui aplikasi berbasis web. Implementasi sistem ini dapat meningkatkan efisiensi penggunaan air hingga 30% dibandingkan dengan metode irigasi konvensional, serta menjaga kelembapan tanah pada tingkat yang optimal untuk pertumbuhan tanaman cabai.
Penerapan Sistem Kontrol Video Tron Di Kampus Politeknik Negeri Bengkalis Berbasis Internet of Things (IoT) Ristra, Pretty; Wahyat, Wahyat; Supria, Supria
TANJAK : Jurnal Pengabdian Kepada Masyarakat Vol 5 No 1 (2024): TANJAK : Jurnal Pengabdian Kepada Masyarakat
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/jj6szh16

Abstract

Politeknik Negeri Bengkalis adalah satu-satunya politeknik negeri yang berada di provinsi Riau. Dalam struktur organisasi Polbeng ada sub  bagian Hubungan Masyarakat Polbeng (Humas Polbeng) yang mengurus urusan informasi, interaksi hubungan ke pihak- pihak terkait. Humas Polbeng merupakan pusat informasi yang berkaitan dengan kegiatan- kegiatan akademis sampai dengan penerimaan mahasiswa baru  dan lain-lain. Pada penelitian sebelumnya telah dibuat suatu alat atau media iklan (video tron) yang dapat menampilkan informasi digital dengan cara mengungah video yang sudah disiapkan ke alat tersebut namun tidak bisa menampilkan video secara online. Tujuan dari kegiatan pengabdian kepada masyarakat yang diusulkan adalah untuk membantu operator menampilkan informasi secara real time, live streaming yang dapat dipantau atau dikendalikan hanya dengan menggunakan smartphone Android melalui jaringan internet. Sehingga operator dapat menggunakan media informasi digital tersebut secara maksimal dan efisien dan tentunya dapat mengikuti perkembangan teknologi yang sedang berkembang saat ini. Metoda yang akan dilaksanakan adalah membuat atau mengganti sebuah kontroller video tron, membangun software development atau megembangankan sebuah aplikasi perangkat lunak yang dijalankan secara sistematis, dapat menampilkan informasi secara real time, live streaming, YouTube dan lain-lain sehingga dapat dipantau atau dikendalikan hanya dengan menggunakan smartphone Android melalui jaringan internet.
Early Warning and Real-Time Ship Tracking using AIS Data and Smartphone GPS Supria, Supria; Wahyat, Wahyat; Ryci Rahmatil Fiska, Ryci Rahmatil Fiska
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/t62fpe35

Abstract

The high risk of maritime accidents in congested waters such as the Malacca Strait requires an affordable safety system specifically for small fishing vessels. This research proposes and evaluates a mobile-based early warning framework that integrates shore-based AIS data with fishermen’s smartphone GPS. The system was tested under 3 operational scenarios using 4G cellular networks over a coastal area of Bengkalis, involving 60 collision simulation events and 180 API requests. Performance evaluation shows an average system latency of 2.3 seconds with a maximum latency of 4.8 seconds. The early warning mechanism successfully detected dangerous proximity (≤50 meters) with an accuracy of 93.3% and an error rate of 6.7%. Position logging via JSON POST achieved a success rate of 96.1% during continuous operation for 2 hours. Although this study demonstrates improved situational awareness and reliable last-known position recording, the system currently uses distance-based detection and does not yet implement CPA/TCPA prediction, which remains future work. The framework contributes as a low-cost monitoring and early warning solution with potential support for SAR operations through reliable historical position data.