Munawar, Iqbal (2018) Analisis sentimen tentang opini masyarakat terhadap Klub Persib Bandung menggunakan metode Naive Bayes Classifier. Diploma thesis, UIN Sunan Gunung Djati Bandung.
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Abstract
INDONESIA: Analisis sentimen akan mengelompokkan polaritas dari teks yang ada dalam kalimat atau dokumen untuk mengetahui pendapat yang dikemukakan dalam kalimat atau dokumen tersebut apakah bersifat positif, negatif atau netral. mengenai review pada akun resmi Persib Bandung yang terdapat pada twitter, dimana menurut web www.jelasberita.com PERSIB adalah satu-satunya klub di Indonesia yang dapat bersaing dengan kepopuleran klub-klub elit Eropa di internet. Tujuan adanya penelitian ini Sistem yang dibangun mampu mengimplementasikan metode Naive Bayes Classifier dalam menentukan kalimat beropini positif dan negatif dan netral terhadap tweet tentang PERSIB lalu menentukan fanatisme terhadap PERSIB di masyarakat dalam media sosial Twitter. Dengan begitu manajemen dapat lebih memperhatikan opini masyarakat sehingga dapat mengetahui mana yang harus dipertahankan dan mana yang harus diperbaiki. Berdasarkan perhitungan akurasi dan error dari hasil klasifikasi maka dari 300 data uji di dapatkan akurasi sebesar 67,67% dan error sebesar 32,32%. Hasil ini menunjukan bahwa algoritma naive bayes classifier dapat bekerja dengan baik dalam menentukan kalimat beropini positif, negatif dan netral terhadap tweet tentang Persib Bandung. ENGLISH: Sentiment analysis will classify the polarity of the text in a sentence or document to find out the opinions expressed in the sentence or document whether they are positive, negative or neutral. regarding a review on the official Persib Bandung account found on twitter, where according to the web www.jelasberita.com PERSIB is the only club in Indonesia that can compete with the popularity of elite European clubs on the internet. The purpose of this study is that the system built is able to implement the Naive Bayes Classifier method in determining positive and negative and neutral opinion sentences against tweets about PERSIB then Determining fanaticism towards PERSIB in the community on Twitter social media. That way management can pay more attention to public opinion so that they can find out which ones must be maintained and which ones must be improved. Based on the calculation of accuracy and errors from the classification results, from 300 test data, it was obtained an accuracy of 67.67% and an error of 32.32%. These results indicate that the naive bayes classifier algorithm can work well in determining positive, negative, and neutral opinion sentences for tweets about Persib Bandung.
Item Type: | Thesis (Diploma) |
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Uncontrolled Keywords: | Implementasi; Naive Bayes Classifier; Persib; Manajemen; Analisis Sentimen;Implementation; Naive Bayes Classifier; Persib; Management; Sentiment Analysis |
Subjects: | Applied Psychology > Interpersonal Relations with Strangers Applied Linguistics > Translating and Interpreting Analysis, Theory of Functions > Analysis and Calculus |
Divisions: | Fakultas Sains dan Teknologi > Program Studi Teknik Informatika |
Depositing User: | mochamad iqbal m |
Date Deposited: | 18 Mar 2019 08:19 |
Last Modified: | 18 Mar 2019 08:19 |
URI: | https://digilib.uinsgd.ac.id/id/eprint/19381 |
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