Analisis Sentimen Menggunakan Metode Naïve Bayes Classifier Dengan Seleksi Fitur Chi Square

Abstract

Sentiment analysis is the computational study of opinions, sentiments, and emotions expressed in texts. The basic task of sentiment analysis is to classify the polarity of the existing texts in documents, sentences, or opinions. Polarity has meaning if there is text in the document, sentence, or the opinion has a positive or negative aspect. In this study, classification of the polarity in sentiment analysis using machine learning techniques, that is Naïve Bayes classifier. Criteria for text classification decisions, learned automatically from learning the data. The need for manual classification is still required because training the data derived from manually labeling, the label (feature) refers to the process of adding a description of each data according to its category. In the process of labeling, feature selection is used and performed by chi-square feature selection, to reduce the disturbance (noise) in the classification. The results showed that the frequency of occurrences of the expected features in the true category and in the false category have an important role in the chi-square feature selection. Then classification breaking news by Naïve Bayes classifier obtained an accuracy of 83% and a harmonic average of 90.713%.

Penerapan Particle Swarm Optimization Terhadap Support Vector Machine Pada Review Pengguna Transportasi Udara

“…Untuk memilih maskapai penerbangan yang sesuai dengan keinginan, calon pembeli dapat melihat opini maskapai penerbangan untuk mengetahui apakah maskapai tersebut sesuai dengan keinginan. Informasi berupa teks merupakan informasi penting dan didapatkan dari berbagai sumber (Ling, N. Kencana, & Oka, 2014).…”

“…Analisis sentimen berguna untuk menganalisis ulasan untuk diterjemahkan menjadi sesuatu yang bermakna (Monarizqa, Nugroho, & Hantono, 2014). Analisis sentimen memiliki tugas mengelompokan polaritas dari suatu dokumen, kalimat atau pendapat (Ling et al, 2014).…”

Penerapan Algoritma Naive Bayes Untuk Analisis Sentimen Pada Wisata TMII Berbasis Website

“…Naive Bayes menerapkan fungsi statistik sederhana berdasarkan teorema bayes dengan asumsi keberadaan dari suatu fitur tertentu terhadap suatu kelas yang tidak berhubungan dengan fitur lainnya (Wilianto, Pudjiantoro, & Umbara, 2017). Naïve Bayes merupakan suatu metode klasifikasi yang menggunakan perhitungan probabilitas (Ling, Kencana, & Oka, 2014).…”

“…Stopwords umumnya digunakan dalam pengambilan informasi salah satu contohnya adalah mesin pencari google. Pengurangan indeks dalam teks dengan penghilangan beberapa kata kerja, kata sifat, dan kata keterangan lainnya dapat dimasukkan ke dalam daftar stopwords (Ling et al, 2014).…”

Review Sentiment Analysis of World Class Hotel Using Naive Bayes Classifier And Particle Swarm Optimization Method

“…Model (Naïve Bayes) is popular in machine learning applications, due to their simplicity in allowing each attribute to contribute against the same final decision, independent of other attributes [7]. Pre-Processing at its testing, Sentiment Analysis uses Naïve Bayes classifier Method with Chi Square Feature Selection [8] as follows:…”