OPTIMASI KLASIFIKASI CURAH HUJAN MENGGUNAKAN SUPPORT VECTOR MACHINE (SVM) DAN RECURSIVE FEATURE ELIMINATION (RFE)
نویسندگان
چکیده
Indonesia merupakan negara tropis yang mempunyai curah hujan tinggi. Curah tinggi dapat mengakibatkan efek samping berupa banjir. Untuk menanggulangi hal tersebut, perlu dilakukan prediksi cuaca akurat. Penelitian ini bertujuan untuk menyelesaikan masalah tersebut dengan mengklasifikasikan kategori sedang dan lebat menggunakan metode data mining CRISP-DM. Algoritma digunakan klasifikasi adalah SVM (Support Vector Machine) optimasi seleksi fitur RFE (Recursive Feature Elimination). Hasil evaluasi Confusion Matrix sebelum menerapkan memiliki akurasi paling besar 77%, setelah meningkat 2% menjadi 79%. Hal menunjukkan penggunaan pada meningkatkan hujan.
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ژورنال
عنوان ژورنال: JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika)
سال: 2022
ISSN: ['2540-8984']
DOI: https://doi.org/10.29100/jipi.v7i2.2675