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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Tech-E JRST (Jurnal Riset Sains dan Teknologi) JITK (Jurnal Ilmu Pengetahuan dan Komputer) JMM (Jurnal Masyarakat Mandiri) Jurnal Media Elektro : Journal of Electrical Power, Informatics, Telecommunication, Electronics, Computer and Control System Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) PROFICIO: Jurnal Pengabdian Masyarakat Bulletin of Information Technology (BIT) International Journal Software Engineering and Computer Science (IJSECS) Journal of Informatics and Communication Technology (JICT) IT For Society : Journal of Information Technology eProceedings of Engineering Innovative: Journal Of Social Science Research Journal of Informatics and Communication Technology (JICT) Smatika Jurnal : STIKI Informatika Jurnal
Dewi Marini Umi Atmaja
Telkom University
Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Public Health Social Sciences Other

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PERAMALAN HARGA MATA UANG KRIPTO SOLANA MENGGUNAKAN METODE SUPPORT VECTOR REGRESSION (SVR) Dewi Marini Umi Atmaja; Arif Rahman Hakim
Jurnal Media Elektro Vol 11 No 2 (2022): Oktober 2022
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jme.v0i0.8117

Abstract

Cryptocurrencies have great potential to be adopted in Indonesia as an alternative to investing. One of the cryptocurrencies that investors or traders are interested in is Solana. Fluctuating price. movements make cryptocurrency investments considered. speculative so the risks. faced are very high. With this, we need a system or model that can help investors or traders to predict prices so that investors or traders have material for consideration in making decisions. The results of the descriptive analysis can be seen that in the period from April 10, 2020 to May 30, 2022, Solana's daily closing price movement fluctuates. The Support Vector Regression model obtained for Solana's daily closing price data, namely the Linear kernel with cost parameter C = 1000, obtained an. accuracy of 97.44% and MAPE 9.93 while for the Radial Basis Function. (RBF) kernel with cost parameter C = 1000 an .gamma = 0.1 obtained an accuracy of 87.76% with a MAPE value of 8.14. It can be concluded that through parameter tuning, the model formed has an accuracy value and the. best MAPE is to use a linear kernel with a cost parameter of C = 1000.
Co-Authors Adelia Chitra Sazkia Adi Kuncoro Adisty Nilasari, Risma Al Zena Ismail Alan Abyan Maftuh Amat Basri Amat Basri Amat Basri Andri Ariyanto Andri Ariyanto Arif Rahman Arif Rahman Hakim Arif Rahman Hakim Arif Rahman Hakim Arif Rahman Hakim Arif Rahman Hakim Arif Rahman Hakim Aufa Hafiy Andhika Basri, Amat Daniswara Rafi Pandora Deny Haryadi Dio Kurnia Sandi Fadhil Rozi Hendrawan Hadiana, Asep Id Haikal Apriandi Ilham Roni Yansyah Jonathan Gunawan Muttaqin, Widang Netanel Danur Wendra Putri Rizkiyah Rila Mandala Rimbawan Oprasto, Raditya Ruaida Susanti Sanjaya, Andreas Rino Suwaryo, Niko Syafii, Muhamad Syifa Nurgaida Yutia Tugiman Tugiman Tugiman Tugiman Wina Witanti Yakub Zaidan Mufaddhal Zhawa Kamela