2020
DOI: 10.12962/j23373520.v8i2.44565
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Analisis Sentimen Nasabah pada Layanan Perbankan Menggunakan Metode Regresi Logistik Biner, Naïve Bayes Classifier (NBC), dan Support Vector Machine (SVM)

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Cited by 7 publications
(7 citation statements)
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“…In addition, there are also several studies that compare several classification algorithms to get the most superior. Some of them are in research [20], [21] compared the Support Vector Machine and Naïve Bayes algorithms to conclude that the Naïve Bayes algorithm is superior because it produces a higher accuracy value. Another study compared the NBC, KNN and Decision Tree algorithms, the analysis resulted in the NBC algorithm producing the highest accuracy value compared to other methods, namely 100% [22].…”
Section: Literature Studymentioning
confidence: 99%
“…In addition, there are also several studies that compare several classification algorithms to get the most superior. Some of them are in research [20], [21] compared the Support Vector Machine and Naïve Bayes algorithms to conclude that the Naïve Bayes algorithm is superior because it produces a higher accuracy value. Another study compared the NBC, KNN and Decision Tree algorithms, the analysis resulted in the NBC algorithm producing the highest accuracy value compared to other methods, namely 100% [22].…”
Section: Literature Studymentioning
confidence: 99%
“…Metode ini akan mentransformasi bentuk teks menjadi bentuk numerik agar dapat digunakan untuk pemodelan. Hasil pembobotan dengan TF-IDF akan diketahui tingkat kepentingan suatu kata terhadap kumpulan twit berdasarkan frekuensi kemunculannya (Sari & Irhamah, 2020). Term Frequency (TF) adalah frekuensi munculnya kata dalam suatu dokumen sedangkan Document Frequency (DF) adalah banyaknya dokumen yang mengandung kata tertentu.…”
Section: Term Frequency-inverse Document Frequency (Tf-idf)unclassified
“…Penelitian ini menjelaskan bagimana metode SVM dan KNN digunakan untuk menganalisis suatu topik berupa "Investasi dimasa pandemic". Metode SVM digunakan untuk pengklasifikasian suatu prediksi dengan memisahkan dua fungsi kelas yang berbeda secara optimal [9]. Sedangkan metode KNN digunakan unurk mencari objek pada data train yang dekat atau mirip dengan data testing [10].…”
Section: Pendahuluanunclassified
“…Pembobotan TF -IDF dilakukan untuk melakukan pembobotan pada model vektor , pembobotan dilakukan untuk mencari frekuensi kemunculannya kata pada kumpulan dataset. TF (Term Frequency) menunjukan frekuensi kata yang muncul, sedangkan IDF(Inverse Document Frequency) menghitung frekuensi kemunculan kata , dengan cara mengalikan TF dengan IDF [9]. Rumus :…”
Section: Pembobotan Tf-idfunclassified