MAHENDRA, ADITYA (2023) ANALISIS SENTIMEN REVIEW PELANGGAN PADA LAYANAN PROVIDER INTERNET MENGGUNAKAN ALGORITMA NAIVE BAYES CLASSIFIER. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
PT Telkom Indonesia as one of the companies that has a network service calledindihome that communicates directly with customers, of course, must be able to know andunderstand very important ratings for services, agencies, products or organizations. PTTelkom Indonesia has problems knowing about customer ratings of indihome services onsocial media. Now PT Telkom Indonesia can only see the assessment by coming in person or calling through customer service. Based on the available conditions and constraints, in thisstudy the researcher conducted a sentiment analysis which would get customer ratings, namely positive, negative and neutral. Customer ratings get data sources from social mediatwitter. In the customer assessment process using the naive Bayes algorithm method. Theresults obtained from sentiment analysis research on data from November 1 2022 toNovember 20 2022 by carrying out 3 scenario stages. The results of all the division datacompositions that have been carried out show a good level of accuracy in the three algorithms. For the Naïve Bayes algorithm, it has the highest level of accuracy in the composition of 80%training data and 20% test data with an accuracy of 79.1139%. Keywords: Sentiment Analysis, Telkom Indonesia, Naïve Bayes, Text Mining PT Telkom Indonesia sebagai salah satu perusahaan yang memliki layananjaringan bernama indihome yang berkomunikasikasi langsung dengan pelangganpastinya harus dapat mengetahui dan mengerti penilaian sangatla penting untuklayanan, instansi, produk atau organisasi. PT Telkom Indonesia memiliki kendaladalam mengetahui terkait penilaian pelanggan kepada layanan indihome pada mediasosial. Sekarang PT Telkom Indonesia baru bisa dapat melihat penilaian dengandatang langsung atau telepon melalui customer service. Berdasarkan kondisi dankendala yang tersedia, maka dalam penelitian ini peneliti melakukan analisis sentimenyang akan mendapatkan penilaian pelanggan, yaitu positive, negative dan neutral. Penilaian pelanggan mendapatkan sumber data dari media sosial twitter. Pada prosespenilaian pelanggan menggunakan metode algoritma naive bayes. Hasil yangdidapatkan dari penelitian analisis sentimen pada data tanggal 1 November 2022hingga 20 November 2022 dengan melakukan 3 tahap skenario. Hasil dari semuakomposisi pembagian data yang telah dilakukan menunjukan tingkat akurasi yangbaik pada ketiga algoritma. Untuk algoritma Naïve Bayes memiliki tingkat akurasi tertinggi pada komposisi 80% data latih dan 20% data uji dengan akurasinya adalah79.1139% Kata Kunci : Analisis Sentimen, Telkom Indonesia, Naïve Bayes, Text Mining
| Item Type: | Thesis (S1) |
|---|---|
| Call Number CD: | FIK/INFO. 23 050 |
| NIM/NIDN Creators: | 41518110093 |
| Uncontrolled Keywords: | Analisis Sentimen, Telkom Indonesia, Naïve Bayes, Text Mining |
| Subjects: | 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika |
| Divisions: | Fakultas Ilmu Komputer > Informatika |
| Depositing User: | MILA RISKA |
| Date Deposited: | 24 May 2023 03:29 |
| Last Modified: | 29 May 2023 09:01 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/77585 |
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