PENERAPAN PRINCIPAL COMPONENT ANALYSIS DAN GENETIC ALGORITHM PADA ANALISIS SENTIMEN REVIEW PENGIRIMAN BARANG MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE

PENERAPAN PRINCIPAL COMPONENT ANALYSIS DAN GENETIC ALGORITHM PADA ANALISIS SENTIMEN REVIEW PENGIRIMAN BARANG MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE

• By Rachmi, Hilda;
• Jurnal Nasional Tidak Terakreditasi
• 200
• 97-104

Analisis sentimen mempelajari pendapat orang, sentimen, sikap, penilaian, evaluasi, dan emosi terhadap entitas seperti produk, layanan, kejadian, organisasi, individu, isu, topik dan atribut. Informasi ini dapat digunakan untuk riset pasar, umpan balik produk dan analisis efektivitas layanan pelanggan. Masalah dalam penelitian ini adalah pemilihan fitur untuk meningkatkan akurasi Support Vector Machine dan menemukan nilai parameter untuk mendapatkan akurasi tertinggi dalam analisis sentimen tinjauan terhadap pengiriman barang serta menghasilkan klasifikasi hasil negatif dan positif dari tinjau dengan tepat Penulis menggunakan Principal Component Analysis dan Genetic Algorithm sebagai optimasi untuk meningkatkan akurasi metode Support Vector Machine. Keakuratan yang dihasilkan dari algoritma Support Vector Machine sebesar 86.00%, setelah dioptimalkan dengan menggunakan Principal Component Analysis dan Genetic Algorithm accuracy telah meningkat menjadi 97%

• Katakunci Analisis Sentimen, Review Pengiriman Barang, Support Vector Machine
• URL https://ejournal.bsi.ac.id/ejurnal/index.php/evolusi/article/view/3130
• Penerbit ,

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