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All Journal Majalah Ilmiah Bahari Jogja Jurnal Riset Teknik Komputer
Muqorobin Muqorobin
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Computer Science & IT Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Transportation Other

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Implementasi Network Intrusion Detection System (NIDS) Dalam Sistem Keamanan Open Cloud Computing Muqorobin Muqorobin; Zul Hisyam; Moch Mashuri; Hanafi Hanafi; Yudhi Setiyantara
Majalah Ilmiah Bahari Jogja Vol 17 No 2 (2019): Juli
Publisher : Sekolah Tinggi Maritim Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (310.076 KB) | DOI: 10.33489/mibj.v17i2.205

Abstract

Security is the most important part of computer network technology systems. Among the technologies that utilize networks are cloud computing. One cloud computing provider such as eucalyptus uses a firewall for system security. The use of a firewall on the system cannot monitor and analyze traffic that is inside the cloud server and does not give a warning when an attack occurs. The purpose of this study is that researchers will implement a network intrusion detection system (NIDS) in cloud computing and mirroring traffic on switches. Intrusion detection system (IDS) is a security technology that can analyze network traffic and detect traffic if an attack is indicated. NIDS are placed hosted differently from cloud computing servers. With the switch mirroring traffic method, traffic will be directed to NIDS so that NIDS can record all network traffic originating from outside the cloud server or traffic between virtual machines within the cloud server. The test results of attacks with 2 scenarios, namely attacks from outside and from within the cloud system, then NIDS is able to provide an alert response to traffic attacks.
IMPLEMENTASI SISTEM PREDIKSI CURAH HUJAN DENGAN PENERAPAN JARINGAN SYARAF TIRUAN BERBASIS WEBSITE Syaifudin Fendi Prasetyo; Tino Feri Efendi; Muqorobin Muqorobin
Jurnal Riset Teknik Komputer Vol. 1 No. 2 (2024): Juni : Jurnal Riset Teknik Komputer (JURTIKOM)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/gn6nym06

Abstract

This research focuses on developing a rainfall prediction system using the Backpropagation Artificial Neural Network (JST) method. The system is designed to predict future rainfall intensity by utilizing four main parameters: air temperature, air humidity, wind speed, and air pressure. Accurate rainfall prediction is essential in various fields, such as agriculture, transportation, and industry. Traditional systems for predicting rainfall are often unable to provide accurate and timely information. Backpropagation JST offers a promising solution to overcome this limitation. The rainfall prediction system developed using Backpropagation JST shows satisfactory performance. The system is able to predict rainfall intensity with a high degree of accuracy. These findings suggest that the Backpropagation JST-based rainfall prediction system can be a valuable tool for various sectors that require accurate and timely rainfall information. The system has the potential to improve efficiency and effectiveness in various activities, such as irrigation planning, disaster risk management, and industrial operations. This research can be extended by exploring other JST methods to improve prediction accuracy. In addition, this research can be implemented in other regions with different climatic conditions to test the generalizability of the system.
RANCANG BANGUN SISTEM PENDETEKSI KEBAKARAN DAN PEMADAM API OTOMATIS BERBASIS INTERNET OF THINGS (IoT) Anggarani, Agustina; Muqorobin Muqorobin; Feri Efendi, Tino
Jurnal Riset Teknik Komputer Vol. 1 No. 2 (2024): Juni : Jurnal Riset Teknik Komputer (JURTIKOM)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/tr6qwt56

Abstract

Fire is an event caused by an uncontrolled ignition source, which generally occurs due to human negligence when using electronic devices without being careful which can cause electrical short circuits and fires. Firefighters often have difficulty extinguishing fires, due to late early detection information regarding fires, so that handling is delayed. Because of this phenomenon, a system is needed that can help prevent fires. This research aims to produce an IoT-based automatic fire detection and fire extinguishing system, as well as to measure and evaluate the system's level of accuracy in detecting fires and responding by extinguishing them. This research will explain the design process for an IoT-based automatic fire detection and extinguishing system, using the System Development Life Cycle Waterfall model research method. The final result of this research is that the author succeeded in creating an Internet of Things (IoT)-based Automatic Fire Detection and Fire Extinguishing System, which is systematically able to detect the presence of fire and gas and perform automatic fire extinguishing functions, and users can also receive notifications via WhatsApp. The author also succeeded in measuring the level of accuracy of the IoT-based automatic fire detection and extinguishing system.
Co-Authors Anggarani, Agustina Feri Efendi, Tino Hanafi Hanafi Moch Mashuri Syaifudin Fendi Prasetyo Tino Feri Efendi Yudhi Setiyantara Zul Hisyam