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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Informatika CommIT (Communication & Information Technology) Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Telematika JUITA : Jurnal Informatika Seminar Nasional Informatika (SEMNASIF) POSITIF Annual Research Seminar Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Jurnal Ilmiah Matrik Jusikom : Jurnal Sistem Komputer Musirawas PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Ilmiah Media Sisfo J-SAKTI (Jurnal Sains Komputer dan Informatika) JURIKOM (Jurnal Riset Komputer) Jurnal Informatika Global Journal of Information Systems and Informatics Jurnal Teknologi Dan Sistem Informasi Bisnis Indonesian Journal of Electrical Engineering and Computer Science Jurnal Teknologi Informatika dan Komputer Jurnal Restikom : Riset Teknik Informatika dan Komputer Journal of Computer and Information Systems Ampera Jurnal Pengembangan Sistem Informasi dan Informatika Journal of Applied Computer Science and Technology (JACOST) Jurnal Nasional Pengabdian Masyarakat J-SAKTI (Jurnal Sains Komputer dan Informatika) International Journal Software Engineering and Computer Science (IJSECS) Jurnal Bina Komputer Indonesian Journal of Innovation Multidisipliner Research Ngabdimas Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer
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Journal : Journal of Information Systems and Informatics

Analysis of Malware Dns Attack on the Network Using Domain Name System Indicators Beni Brahara; Dedy Syamsuar; Yesi Novaria Kunang
Journal of Information System and Informatics Vol 2 No 1 (2020): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/journalisi.v2i1.30

Abstract

University of Bina Darma Palembang has its own DNS server and in this study using log data from the Bina Darma University DNS server as data in the study, DNS log server data is analyzed by network traffic, using Network Analyzer tools to see the activity of a normal traffic or anomaly traffic, or even contains DGA Malware (Generating Algorthm Domain).DGA malware produces a number of random domain names that are used to infiltrate DNS servers. To detect DGA using DNS traffic, NXDomain. The result is that each domain name in a group domain is generated by one domain that is often used at short times and simultaneously has a similar life time and query style. Next look for this pattern in NXDomain DNS traffic to filter domains generated algorithmically that the domain contains DGA. In analyzing DNS traffic whether it contains Malware and whether network traffic is normal or anomaly, in this study it detects Malwere DNS From the results of the stages of the suspected domain indicated by malware, a suspected domain list table is also created and also a suspected list of IP addresses. To support the suspected domain analysis results, info graphic is displayed using rappidminer tools to test decisions that have been made using the previous tools using the Decision Tree method.
Sentiment Analisis Terhadap Cryptocurrency Berdasarkan Comment Dan Reply Pada Platform Twitter Adam Prasetya; Ferdiansyah Ferdiansyah; Yesi Novaria Kunang; Edi Surya Negara; Winoto Chandra
Journal of Information System and Informatics Vol 3 No 2 (2021): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/journalisi.v3i2.124

Abstract

Analisis sentiment saat ini banyak di gunakan masyarat sebagai bahan untuk mengetahui pendapat atau opini masyarakattentang berbagai macam hal. Dengan menggunakan sentiment analisis kita dapat mengklasifikasikan data apakah data tersebuttermasuk opini netral opini positif opini negatif. Penelitian ini membahas tentang analisis sentiment untuk mengukur tingkatakurasi dari pendapat masyarakat pada tiga cryptocurrency yaitu Bitcoin,ethereum,ripple dengan metode Naive Bayes dansupport vector machine yang berguna untuk mengetahui nilai akurasi yang tertinggi dari dua metode yang digunakan dalampenelitian ini. Ada banyak metode yang bisa digunakan untuk mengkasifikasikan opini tersebut, namun penelitian ini dipilihmetode Naive Bayes dan Support vector machine, dengan alasan metede tersebut banyak di gunakan oleh peneliti lain danmenghasilkan nilai akurasi yang tinggi. Hasil dari penelitian ini adalah berupa data perbandingan dari akurasi. hasil akurasidari 3 cryptocurrency SVM lebih besar dari pada nilai akurasi 3 cryptocurrency Naive Bayes.
Machine Learning-Based E-Archive for Archives Management of South Sumatra Province Atmojo, Toni Tri; Kunang, Yesi Novaria
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.566

Abstract

Archives play a crucial role in institutional operations, yet efficiently retrieving specific information from them can be challenging. This research addresses this issue by developing an information retrieval system that incorporates advanced methods to enhance search efficiency. The system employs the TF-IDF (Term Frequency-Inverse Document Frequency) formula, which assesses the significance of a word within a document set, and the BM25 method, a sophisticated algorithm for ranking documents based on their relevance to the input query. Both methods undergo a preprocessing stage, enabling the system to calculate the relevance of each document to the given query accurately. The effectiveness of this system is evaluated using key performance metrics: precision (accuracy), recall (completeness), and the F1 Score (the harmonic means of precision and recall, representing the best value). Testing with various keywords revealed that the BM25 method yielded impressive results, achieving an average precision of 0.75, recall of 0.6, and an F1 Score of 0.6665. In contrast, the TF-IDF method scored lower, with a precision of 0.33, recall of 0.2, and an F1 Score of 0.2500. The system was tested using a dataset of 350 documents.
Rule-Based Transliteration of Ulu Kaganga Script using Character Mapping Yadi, Ilman Zuhri; Kunang, Yesi Novaria; Sari, Tia Permata; Mahmud, Mahmud; Ramadhona, Nuzulur
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.1000

Abstract

Ulu Kaganga script is a historical writing tradition that developed in the southern region of Sumatra. With the widespread use of Latin script, the Ulu Kaganga script has become rare, and very few people can read and write in this script. To preserve the Ulu script, a tool is needed to assist in transliterating Latin text into the Ulu script. This research aims to preserve the Ulu script with the help of technology. In this study, a mobile and web-based application has been developed to transliterate the Ulu Kaganga script from Latin text. The technique used for this script conversion is rule-based, which is employed to break words into syllables and map those syllables into Ulu script characters. Through the rule-based technique and character mapping, adding Indonesian syllables and writing Ulu Kaganga script characters, consisting of 1139 primary characters, becomes easy. This application has been repeatedly tested to improve the mapping of Ulu script characters. The results of testing the application to transliterate 1746 words from Latin script were successful in transliterating. The tests conducted show that the approach used is very effective, with a transliteration accuracy from Latin to Ulu script of 99.98% The testing results show that the application can transcribe text accurately and conveniently, allowing non-expert users to write in Ulu script characters.
Co-Authors Adam Prasetya Afiyudi, Afiyudi Afriyudi Agus Setiawan Agus Setiawan Ahmad Zarkasi Andika, Muhamad Andri Andri Anggie Khristian Ariandi, Muhamad Arief Algiffary Armansyah, Risky Atmojo, Toni Tri Ayu Okta Pratiwi Beni Brahara Bhakti Yudho Suprapto Damayanti, Nita Rosa Darmawahyuni, Annisa Dedy Syamsuar Dedy Syamsuar Deris Stiawan Dinata, Aria Dzakwan, Fadhlur Rahman Edi Surya Negara Egy Septian Eka Puji Agustini Endang Etriyanti Fajarino, Aldo Ferdiansyah Ferdiansyah Fernandy Jupiter Fikri, M Finaldo, Muhammad Firdaus Firdaus Firdaus Fitri maria Gllen yusuf abbel Hamanrora, Muhammad Dio Hellen Puspita Sari Hendra Marta Yudha Herdiansyah, Izman Herdiansyah, M. Izman Herferry, Ibrahim Ade Ilman Zuhri Yadi Ilman Zuhri Yadi Ilman Zuhriyadi Inda Anggraini Irwansyah Ibrahim Kurniawan Kurniawan Lang Dimas Perkasa Leon Andretti Abdillah Liza Fahreni M Izman Herdiansyah M. Izman Herdiansyah Mahmud Mahmud Mahmud Mahmud Muhammad Fachrurrozi Muhammad Hafiz Ziqrullah Muhammad Izman Herdiansyah Muhammad Naufal Rachmatullah Netti Herawati Novi Yusliani Novifika, Seva Permatasari, Susan Dian Prasetya, M. Iqbal Prilsafira, Tania Putra, Muhammad Hatta Ramadhona, Nuzulur Rianda, M. Rianda Rio Ananda Fitriansyah Sari, Tia Permata Siti Nurmaini Sri Murniati Suryayusra - Susan Dian Purnamasari, Susan Dian Taqrim Ibadi Tata Sutabri Tia Permata Sari Toriko, Liu Tri Basuki Kurniawan Tri Basuki Kurniawan Usman Ependi Via Sukma Cendanie Widya Cholil Widya Putri Mentari Winoto Chandra Wulandari, Intan Fitriana Yayuk Ike Meilani Yudi, Endang Darmawan Yustida Bellini Zulkifli Harahap Zulkifli Harahap