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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA J-SAKTI (Jurnal Sains Komputer dan Informatika) JURIKOM (Jurnal Riset Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) J-SAKTI (Jurnal Sains Komputer dan Informatika) BEES: Bulletin of Electrical and Electronics Engineering Journal of Computer Science and Information Technology Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Aldisa, Rima Tamara
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Environmental Science Industrial & Manufacturing Engineering Social Sciences

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Journal : Journal of Computer System and Informatics (JoSYC)

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Penerapan Metode Support Vector Machine Dalam Memprediksi Prediksi Cuaca Rifqi, Muhammad Naufal; Aldisa, Rima Tamara
Journal of Computer System and Informatics (JoSYC) Vol 5 No 2 (2024): February 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i2.4961

Abstract

Weather is a natural that has a big impact on humans. Information about weather predictions is really needed by humans, especially in the city of Medan. This information is very useful for knowing weather events around us. Data mining is a process of collecting important information from large data, so that it can help make decisions and make accurate predictions. So researchers are interested in conducting research in predicting the weather in the city of Medan using the Support Vector Machine (SVM) method as a solution for predicting the weather in the city of Medan. The application of data mining using the SVM method helps produce precise accuracy for weather based on predetermined criteria. This method is suitable for weather predictions because it is able to provide clear and accurate assessments with weather predictions of 54.55%.
Co-Authors Abdullah, Mohammad Aldinugroho Abdullah, Syamsun Nahar Ade Davy Wiranata Ahmad Rifqi Aldinugroho, Mohammad Alfarisi, Sechan Andrianingsih Azizah Azizah Fadhilah, Raihan Fajar Fadillah, Rizkah Faran, Jhiro Fauziah Fauziah Ghirrid, Aria Andros Iskandar Fitri, Iskandar Kaka, Siprianus Rendi Karel, Fhizyel Nazareta Maulana, Pandu Mesran, Mesran Nasution, Aisah Amini Putra, Gifari Yudiya Putra, Ricky Syah Rafli, R Rangkuti, Wanda Tofani Devi Ratih Titi Komalasari Rifqi, Muhammad Naufal Romadhon, Raihansa Sari, Cindy Nanda Sembiring, Rinawati Septi Andryana Sholeha, Puspa Ayu Sholihati, Ira Diana Wahyuddin, Mohammad Iwan Zikrullah, Alhadi Putra