Analisis Kinerja NLP dan Support Vector Machine Untuk Klasifikasi Intent Chatbot Administrasi Toko Koperasi
DOI:
https://doi.org/10.29407/vz0gg812Abstract
Penelitian ini membahas penerapan Natural Language Processing (NLP) dan Support Vector Machine (SVM) untuk klasifikasi intent pada chatbot administrasi toko koperasi. Permasalahan utama yang dihadapi adalah banyaknya variasi kalimat pengguna ketika menanyakan harga, stok, harga reseller, serta perintah perubahan data barang. Dataset berasal dari file Excel yang berisi 179 baris data mentah dengan delapan kolom intent, kemudian ditransformasikan menjadi 836 data teks berlabel. Tahap preprocessing mencakup case folding, pembersihan tanda baca, normalisasi kata tidak baku, penghapusan stopword, serta pembentukan teks bersih. Fitur teks dibentuk menggunakan TF-IDF unigram dan bigram, sedangkan proses klasifikasi dilakukan menggunakan LinearSVC dengan pembagian data 80:20. Hasil pengujian menunjukkan bahwa model memperoleh akurasi sebesar 88,10% pada data testing dan rata-rata akurasi cross validation sebesar 90,08%. Hasil ini menunjukkan bahwa kombinasi NLP, TF-IDF, dan SVM mampu mengenali intent chatbot koperasi secara cukup baik serta dapat digunakan sebagai dasar pengembangan chatbot cerdas pada sistem administrasi koperasi.
Keywords:
chatbot, koperasi, klasifikasi intent, NLP, SVM##plugins.themes.default.displayStats.downloads##
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