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All Journal Brilliance: Research of Artificial Intelligence Digital Transformation Technology (Digitech)
Huda, Moh Abroril
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Computer Science & IT Decision Sciences, Operations Research & Management Library & Information Science Mathematics Other

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Computer Network Management Optimization Through Big Data Analysis Using Time Series Analysis Method Putra, Fauzan Prasetyo Eka; Ubaidi, Ubaidi; Huda, Moh Abroril; Hasbullah, Hasbullah; Rohman, Abd
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4373

Abstract

Efficient management of computer networks is becoming increasingly important in the ever-evolving digital age. With the ever-increasing volume of data in the network environment, sophisticated approaches are needed to analyse and optimise network performance. One promising approach is the use of big data analysis with time series analysis methods. In this context, this research aims to explore the potential application of big data analysis using the time series analysis method in computer network management. By combining the power of big data analysis with time series analysis methodology. One of the main applications of  big data analysis in computer networks is security threat detection. By analysing unusual traffic patterns or suspicious behaviour, the system can identify potential attacks or data leaks more quickly and efficiently. In addition, big data analytics can also be used to optimise network performance by identifying bottlenecks, predicting capacity requirements, and improving the efficiency of resource usage by utilising big data analytics in the context of computer networks. However, challenges related to data privacy and security remain a major concern that must be addressed in the application of this technology. Therefore, it is important to develop a framework that takes into account the security and privacy aspects of data throughout the big data analysis process. Through this research, it is hoped that innovative solutions to the challenges of managing complex computer networks in the evolving digital era can be found, as well as provide a solid foundation for further research in this field.
Computer Network Management Optimization Through Big Data Analysis Using Time Series Analysis Method Putra, Fauzan Prasetyo Eka; Ubaidi, Ubaidi; Huda, Moh Abroril; Hasbullah, Hasbullah; Rohman, Abd
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4373

Abstract

Efficient management of computer networks is becoming increasingly important in the ever-evolving digital age. With the ever-increasing volume of data in the network environment, sophisticated approaches are needed to analyse and optimise network performance. One promising approach is the use of big data analysis with time series analysis methods. In this context, this research aims to explore the potential application of big data analysis using the time series analysis method in computer network management. By combining the power of big data analysis with time series analysis methodology. One of the main applications of  big data analysis in computer networks is security threat detection. By analysing unusual traffic patterns or suspicious behaviour, the system can identify potential attacks or data leaks more quickly and efficiently. In addition, big data analytics can also be used to optimise network performance by identifying bottlenecks, predicting capacity requirements, and improving the efficiency of resource usage by utilising big data analytics in the context of computer networks. However, challenges related to data privacy and security remain a major concern that must be addressed in the application of this technology. Therefore, it is important to develop a framework that takes into account the security and privacy aspects of data throughout the big data analysis process. Through this research, it is hoped that innovative solutions to the challenges of managing complex computer networks in the evolving digital era can be found, as well as provide a solid foundation for further research in this field.
Analisis Keamanan Jaringan Dari Serangan Malware Menggunakan Filtering Firewall Dengan Port Blocking Zulfikri, Achmad; Putra, Fauzan Prasetyo Eka; Huda, Moh Abroril; Hasbullah; Mahendra; Miftahus Surur
Digital Transformation Technology Vol. 3 No. 2 (2023): Artikel Periode September 2023
Publisher : Information Technology and Science(ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/digitech.v3i2.3379

Abstract

Jaringan komputer memiliki peranan penting dalam kegiatan belajar mengajar di sekolah, akan tetapi adapula dampak negatif yang ditimbulkan. Salah satunya rawan di serang oleh malware seperti virus dan lain sebagainya. Berdasarka permasalahan tersebut maka dilakukan penelitian yang bertujuan untuk mengatasi permasalahan-permasalahan disebabkan oleh penyebaran malware yang terdapat dalam jaringan. Salah satu dampak adanya malware dalam jaringan kampus adalah overload traffic bandwidth, sehingga menyebabkan kendala bandwidth yang cepat habis atau lalu lintas transfer data baik yang masuk maupun yang keluar menjadi lambat dari biasanya. Umumnya sebuah kampus atau universitas memiliki struktur jaringan yang didalamnya dikelola oleh satu atau lebih router di dalam mengelola jaringan dan bandwidth. Beberapa router memiliki kemampuan pengaturan firewall yang sudah cukum mumpuni namun perlu dikelola lebih spsesifik berdasarkan kebutuhan skala jaringan dan bandwidth yang tersedia. Dengan menciptakan rule-rule yang baik di dalam firewall akan lebih mudah dalam melakukan filtering terhadap lalu lintas trafik jaringan dan bandwidth sehingga dapat menciptakan keamanan dan kenyamanan pengguna jaringan dan bandwidth. Hasil penelitian ini menunjukkan kinerja dari mikrotik router board RB 1100 AHx2 yang dapat memfilter aktivitas malware dengan rule yang telah ditanamkan
Co-Authors Abd Rohman, Abd Fauzan Prasetyo Hasbullah Hasbullah Hasbullah Mahendra Miftahus Surur Ubaidi, Ubaidi Zulfikri, Achmad