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All Journal JUSIFO : Jurnal Sistem Informasi Jurnal Ilmiah KOMPUTASI JUTIM (Jurnal Teknik Informatika Musirawas) Journal of Information Systems and Informatics Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Jurnal Sistem Komputer dan Informatika (JSON) Journal of Information Technology Ampera Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) J-SAKTI (Jurnal Sains Komputer dan Informatika)
Ferdiansyah Ferdiansyah
Universitas Bina Darma
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Energy Engineering Other

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Studi Performa Migrasi Ipv4 Ke Ipv6 Pada Metode Tunneling Mukti, Aan Restu; syah, Ferdian
JUTIM (Jurnal Teknik Informatika Musirawas) Vol 2 No 1 (2017): JUTIM (JURNAL TEKNIK INFORMATIKA MUSIRAWAS) JUNI
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (574.551 KB) | DOI: 10.32767/jutim.v2i1.28

Abstract

Dengan ketersedian (space) dari pengalamatan IPv4 yang telah sedikit, itu telah menjadi alasan utama bagi penyedia layanan, perusahaan, pengembang aplikasi, dan pemerintah untuk memulai beralih dengan IPv6. Sebuah migrasi dari IPv4 ke IPv6 sulit dicapai. Karena beberapa mekanisme yang diperlukan untuk menjamin kelancaran, komunikasi dan peralihan secara utuh ke IPv6. Tidak hanya transisi, integrasi IPv6 juga diperlukan ke dalam jaringan yang ada. Solusi (mekanisme) dapat dibagi menjadi tiga kategori: dual stack, tunneling dan translation. Dalam proyek ini mekanisme transisi Tunneling diimplementasikan di GNS3 (Graphical Network Simulator), menggunakan CISCO router.Jaringan ini dilihat dengan bantuan Wireshark (Packet analyzer). Topologi Tunneling yang dapat diamati dengan menangkap paket pada interface router.
BITCOIN-USD TRADING USING SVM TO DETECT THE CURRENT DAY’S TREND IN THE MARKET Ferdiansyah Ferdiansyah; Edi Surya Negara; Yeni Widyanti
Journal of Information System and Informatics Vol 1 No 1 (2019): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/journalisi.v1i1.7

Abstract

Bitcoin is a kind of Cryptocurrency and now is one of type of investment in the stock market. Stock markets are influenced by many risks of factor. And bitcoin is one kind of cryptocurrency that keep rising in recent few years, and sometimes fall without knowing influence behind it, on stock market. Because it’s fluctuations, there’s a need Automated tool to prediction of bitcoin on stock market. However, because of its volatility, there’s a need for a prediction tool for investors to help them consider investment decisions for bitcoin or another cryptocurrency trade. The predict methods will be used on this research is regime prediction to develop model to predict trend at the opening of market using SVM.
A Study of Economic Value Estimation on Cryptocurrency Value back by Gold, Methods, Techniques, and Tools Ferdiansyah Ferdiansyah; Siti Hajar Othman; Raja Zahilah Md Radzi; Deris Stiawan
Journal of Information System and Informatics Vol 1 No 2 (2019): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/journalisi.v1i2.25

Abstract

After Bitcoin Introduced around the world, many Cryptocurrencies was created that followed the standard of bitcoin. The use of Bitcoin or other Cryptocurrency as a currency is also an interesting study from an Islamic economic perspective. They tried to use gold with value back by gold , which gold itself is famous for its exchange rate stability. From abu bakar There is a need for monitoring organization of the cryptocurrency, to controlling from Riba (Interest), Maysir (gambling) and ghahar (Uncertainty). To solve this problem there is a need a tool that can predict with certainty based on valid historical data, to produce accurate prediction results and produce Economic value estimations that are close to Gold real value. With the results we can monitoring day by day, see next day value and continuously based on Cryptocurrency with value back by gold, and see what other impact influences the value by looking the factor negative or positive with sentiment analysis. In the last section we discuss and provide method that we analyse from previous work to produce method to estimate value cryptocurrency value back by gold.
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.
Analisis Aktivitas dan Pola Jaringan Terhadap Eternal Blue & Wannacry Ransomware Ferdiansyah Ferdiansyah
JUSIFO : Jurnal Sistem Informasi Vol 4 No 1 (2018): JUSIFO (Jurnal Sistem Informasi) | June 2018
Publisher : Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Raden Fatah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19109/jusifo.v4i1.2077

Abstract

Internet memainkan perananan sangat penting saat ini dalam kehidupan dengan pertumbuhan yang cepat harus pula di ikuti dengan meningkatkan kewaspadaan terhadap ancaman siber. Wannacry dan Eternal blue adalah salah satu ancaman kejahatan siber yang sangat besar karena banyak sekali dampak serta kerugian yang ditimbulkan. Penelitian ini diharapkan dapat membantu dalam mengetahui aktivitas dan pola serangan Eternal blue dan Wannacry Ransomware beraksi pada jaringan dan bagaimana Malware mengeksploitasi korban.
Penerapan Ontology Berbasis Protégé Untuk Mengestimasi Nilai Ekonomi Cryptocurrency Muhammad Ashardiansyah Putra; Ferdiansyah Ferdiansyah; Linda Atika; Kiky Rizky Nova Wardani
Journal of Information Technology Ampera Vol. 2 No. 2 (2021): Journal of Information Technology Ampera
Publisher : APTIKOM SUMSEL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalita.volume2.isssue2.year2021.page77-89

Abstract

Cryptoccurency is a digital currency that is used as a medium of exchange as well as rupiah and dollars. And just like currency, Cryptocurrency also experiences value volatility or commonly reffered to as fluctuation. The purpose of this study is to estimate the fluctuating cryptocurrency value by implementing it into ontology using protégé tools. With the ontology, it can make it easier for users to find information about cryptocurrency. The results of this study indicate that ontology is one of the bases of Knowledge Managament Systems which can make it easier to systematizem, improve and accelerate knowledge management so that it is easy to understand for cryptocurrency users. Another result of this research is the creation of an ontology cryptoccurency with the blockchain subclass, users, currency, economu and factors. Each of these subclasses has more subclasses in a structured manner, and the results of making computer technique ontology in estimating the economic value of cryptocurrency are useful for users or people who want to find out more information about cryptocurrency.
Analisis Log Menggunakan Jupyter Notebook pada Kasus Cyber Threat Hunting Sutra Ovi Yansa; Ferdiansyah
Jurnal Ilmiah KOMPUTASI Vol. 21 No. 2 (2022): Jurnal Ilmiah Komputasi Volume: 21 No. 2, Juni 2022
Publisher : Lembaga Penelitian STMIK Jakarta STI&K

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Forensik Digital merupakan disiplin ilmu yang menerapkan investigasi dan identifikasi dalam menindak kejahatan digital. Salah satu tahapan utama dalam menginvestigasi tindak kejahatan yaitu mengumpulkan barang bukti digital. Untuk menemukan barang bukti digital pada malware, dibutuhkan analisis lebih mendetail agar dapat mendeteksi aktifitas sebuah malware serta mempelajari bagaimana sebuah malware menginfeksi dan berkembang dalam sebuah sistem . Ada dua tipe analisis dalam melakukan analisis pada malware yaitu dengan analisis statis (analisa kode) dan analisis dinamis. Meskipun dari kedua tipe analisis tersebut mempunyai tujuan yang sama yaitu menjelaskan tentang bagaimana sebuah malware bekerja namun peralatan, waktu dan kemampuan yang dibutuhkan dalam menganalisa sangatlah berbeda. Dengan memanfaatkan events log dapat membantu dalam proses analisis sebuah malware dengan melihat setiap peristiwa yang telah disimpan serta dikelola lebih jauh menggunakan aplikasi open source seperi jupyter notebook yang dapat menghasilkan bukti digitial berupa visualisasi IP serangan terhadap sistem dan dapat dipertanggung jawabkan pada persidangan.
Deep Learning Model Analysis and Web-Based Implementation of Cryptocurrency Prediction Gege Ardiyansyah; Ferdiansyah Ferdiansyah; Usman Ependi
Journal of Information System and Informatics Vol 4 No 4 (2022): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v4i4.365

Abstract

Cryptocurrency is a digital asset designed by cryptography, such as Secure Hash Algorithm 2 (SHA-2) and Message Digest 5 (MD5). Cryptocurrency uses Blockchain technology to ensure security, transparency, ease of locating, and unchangeability. This makes cryptocurrency very popular in many sectors, especially in the financial industry. Although, the uncertainty and the dynamic change of cryptocurrency price make the risk for investment in this digital asset high. This is the reason why studies about cryptocurrency price prediction became popular globally. This study intended to predict cryptocurrency prices using hybrid GRU LSTM than setting up the epoch to get the most accurate prediction model. The researcher would make a web-based application that can be used by the public, especially those involved in cryptocurrency investment. The result was a web-based application that could predict the price of cryptocurrency for the next few days, which had been validated using data from the previous 7 days, 14 days, 30 days, 60 days, and 90 days.
Analisis Data Mining Klasifikasi Berita Hoax COVID 19 Menggunakan Algoritma Naive Bayes Fani Prasetya; Ferdiansyah Ferdiansyah
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 1 (2022): September 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4852

Abstract

The rapid dissemination of information along with the rapid development of technology along with the massive speed of electronic media and the internet. But the rapid spread of news cannot guarantee that the information and news that we get can be validated from valid sources. Based on data released by Kominfo at the end of 2021, there were 1773 hoax news that were successfully clarified from the hoax news. Then during the Covid-19 pandemic itself, there were various hoaxes circulating in the community. Throughout 2021, the Ministry of Communications and Informatics discovered as many as 723 hoaxes about Covid-19. Based on the background above, the researchers and previous studies have discussed hoax detection in various fields. Such as, fraud detection in online writing style [1], classification of hoax news based on machine learning [3] and the application of nave Bayes and PSO algorithms for classification of hoax news on social media [4]. From here the researchers tried to carry out experiments on the nave Bayes classification algorithm to classify hoax covid 19 news. Based on the results of research that has been done, the nave Bayes model and cross validation can classify hoax news well, the resulting accuracy is 86.3% where 80-90% included in the good classification criteria. The data that is predicted to be incorrect is also not too much from a total of 300 datasets, only 41 are declared incorrect in labeling less than 2% of the total dataset, so it can be concluded that this model can be used as a reference if you want to proceed to a more complex prediction model, for example the model prediction using web-based machine learning.
Implementasi Algoritma K-Nearest Neighbors Pada Penentuan Jurusan Siswa M. Daffa Alkhussayid; Ferdiansyah Ferdiansyah
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 1 (2022): September 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4759

Abstract

SMA Negeri 8 Palembang has two majors, namely science and social studies. Determination of majors is done when in class X to determine the majors of the student. This research was conducted because the teacher had difficulty in determining the majors at SMA Negeri 8 Palembang. In the research case, the researcher uses the classification with the k-Nearest Neighbors algorithm, and the Euclidean distance measurement method to predict the students in determining the majors that will be taken by students. The source of the data for this research is the report card scores for the X grade students of SMA Negeri 8 Palembang, and the data for this research are 335 data on the grade X students of SMA Negeri 8 Palembang. The data collection was taken from the grade X class report cards, namely mathematics, physics, biology, English, Indonesian, history, geography, economics, and psychological test scores. In determining the majors, students in science and social studies get the average score of all subjects and the psychological test scores produced by these students to enter the science department with an average score of 80, math score 78, physics 78, biology 78, and psychological test 80. If students get an average score below 80, it will be predicted to enter social studies, to enter the social studies department with a minimum score of 70 geography subjects, 70 economics, 70 history, and 70 psychological test scores. The results obtained in this study used the K method. -Nearest Neighbors based on training data obtained from 335 student data, 101 classified social studies class according to predictions, 10 data predicted social studies, but data declared natural science, 2 science prediction data and, 222 data according to natural science predictions, and the accuracy got 96% and the results of observations using the Website using K-NN show the same data results obtained through an accuracy of 96%.
Co-Authors A Andri Aan Restu Mukti, Aan Restu Adam Prasetya Andreean Dharma Arisandi Aziz Awaludin Briandy Tri Putra Briandy Deris Stiawan Edi Surya Negara Evi Yulianingsih Fani Prasetya Fatmasari Fatmasari Gege Ardiyansyah Ilham budiman Kiki Rizky Nova Wardani kiky rizky nova wardani Linda Atika Linda Atika M. Daffa Alkhussayid Muhammad Ashardiansyah Putra Raja Zahilah Md Radzi Rangga Yogasuwara Siti Hajar Othman Sutra Ovi Yansa Tri oktarina Usman Ependi Winoto Chandra Yeni Widyanti Yesi Novaria Kunang