Firdausi, Inayah Eka (2019) Analisis Sentimen Tanggapan Pelanggan Operator Telekomunikasi di Twitter dengan Algoritma DCNN-SVM. Other thesis, Institut Tekhnologi Sepuluh Nopember.
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Abstract
Seiring perkembangan zaman, media sosial banyak diminati oleh berbagai kalangan masyarakat karena media sosial memungkinkan penggunanya untuk mengungkapkan pikiran atau perasaan mereka secara bebas. Penting bagi sebuah perusahaan untuk mengetahui tanggapan publik mengenai produk atau layanan yang ditawarkan. Dengan tanggapan publik ini, perusahaan dapat menganalisis kebutuhan pelanggan dan membuat perencanaan produk atau layanan yang lebih memuaskan. Untuk dapat mengetahui sentimen dari tanggapan, maka perlu pengklasifikasian tanggapan. Oleh karena itu, pada penelitian ini digunakan metode Deep Convolutional Neural Network (DCNN) sebagai pengekstraksi fitur dan Support Vector Machine (SVM) sebagai pengklasifikasiannya. Hasil performansi dari penelitian ini yaitu akurasi data uji sebesar 63%, presisi data uji sebesar 63% dan recall data uji sebesar 50%.
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Along with the development of the times, social media is in great demand by various circles of society because social media allows users to express their thoughts or feelings freely. It is important for a company to know public responses about the product or service offered. With this public response, companies can analyze customer needs and plan more satisfying products or services. To be able to know the sentiments of responses, it is necessary to classify responses. Therefore, in this study used the Deep Convolutional Neural Network (DCNN) method as a feature extraction and Support Vector Machine (SVM) as its classification. The performance results of this research are 63% for accuracy of test data, 63% for precision of test data and 50% for recall of test data.
| Item Type: | Thesis (Other) |
|---|---|
| Additional Information: | RSMa 005.1 Fir a-1 2019 |
| Uncontrolled Keywords: | Analisis Sentimen, Deep Convolutional Neural Network, Support Vector Machine, Twitter |
| Subjects: | Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science) Q Science > QA Mathematics > QA76.9.D343 Data mining. Querying (Computer science) |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Chemistry > 47201-(S1) Undergraduate Thesis |
| Depositing User: | Inayah Eka Firdausi |
| Date Deposited: | 27 Sep 2024 10:24 |
| Last Modified: | 27 Sep 2024 10:24 |
| URI: | http://repository.its.ac.id/id/eprint/69161 |
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