PERBANDINGAN KINERJA ALGORITMA NAIVE BAYES DAN SUPPORT VECTOR MACHINES DALAM KLASIFIKASI ULASAN RESTORAN
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Tujuan dari penelitian ini adalah untuk membandingkan kinerja antara kedua algoritma, naive bayes dan support vector machine (SVM), dalam konteks penelitian ini, yang dibahas ialah klasifikasi ulasan restoran. Kedua algoritma ini adalah pilihan yang terbilang populer untuk bidang machine learning sebab kemampuan mereka yang mampu melakukan klasifikasi dan prediksi data dengan akurat. Dataset pada penelitian ini diperoleh dari website Kaggle, di mana ulasan positif diberi nilai 1 dan ulasan negatif diberi nilai 0. Melalui percobaan eksperimen ini algoritma yang mendapatkan akurasi klasifikasi paling besar ialah Support Vector Machine sebesar 77.89%, sedangkan naive bayes hanya mendapatkan akurasi klasifikasi sebesar 72.86%. Analisis klasifikasi perbandingan ini meliputi evaluasi metrik seperti akurasi, presisi, recall, f1-score, dan support. Diharapkan hasil penelitian ini dapat memberikan wawasan yang berharga untuk pemilihan kedua algoritma klasifikasi untuk tugas klasifikasi ulasan restoran.
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