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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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Journal : Journal of Information Systems and Informatics

 1 
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.
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.
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