Sentimen Analisis Rumah Makan Rawon Sakinah Dengan Metode Naïve Bayes Classifier
Keywords:
Analisis Sentimen, Metode naive bayes classifierAbstract
Abstract-Rawon Sakinah Restaurant is a famous restaurant in the city of Pasuruan. If you are looking for typical culinary delights from Pasuruan City, local residents will unanimously answer Rawon Sakinah. This restaurant has been around for 30 years. located at Jalan Bangilan No. 80 Pasuruan City. In this study, the sentiment of visitors to the Rawon Sakinah Restaurant will be analyzed based on Google reviews. To find out the reviews of visitors to the Rawon Sakinah Restaurant whether the sentiment reviews are positive or negative. The stages of data analysis are text processing to clean data, weighting words, labeling data into positive and negative classes, classifying, and visualizing data with wordcloud. positive sentiments amounted to 237 and negative sentiments amounted to 13. In this study using the Naïve Bayes method. The accuracy value obtained for the Naïve Bayes method is 92% with a positive sentiment. From the results of the review sentiment research, it was found that the majority of visitors had positive sentiments.
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Afifah, Adilla. 2015. “Respon Pelanggan Pada Situs Tripadvisor.Com Sebagai Bentuk Cyber Public Relations The Premiere Hotel Pekanbaru.” Jom FISIP Universitas Riau2(2):2.
Agung, I. Gusti Ngurah. 2000. “Analisis Statistik Sederhana Untuk Pengambilan Keputusan.” Jurnal Populasi Kependudukan Dan Kebijakan Universitas Gadjah Mada 11(2):77.
Alif, Faris Zharfan. 2020. “Ekstraksi Fitur Untuk Pemilihan Topik Spesifik Review Film Dalam Menghasilkan Aspect-Based Sentiment Analysis.” Univsersitas Sumatera Utara 6. ASH. 2020. “TFIDF Separate for Each Label.” Stack Overflow. Retrieved June 2, 2020 (https://stackoverflow.com/questions/60686556/tfidf-separate-for-eachlabel).
Bedi, Gunjit. 2018. “A Guide to Text Classification(NLP) Using SVM and Naive Bayes with Python.” Medium. Retrieved July 27, 2002 (https://medium.com/@bedigunjit/simple-guide-to-text-classification-nlp-usingsvm-and-naive-bayes-with-python-421db3a72d34).
Billy Gunawan, Helen Sastypratiwi, Enda Esyudha Pratama. 2018. Sistem Analisis Sentimen pada Ulasan Produk Menggunakan Metode Naive Bayes. http://dx.doi.org/10.26418/jp.v4i2.27526
Darmawidjadja, and Dion Alamsah. 2017. “Klasifikasi Untuk Diagnosa Diabetes Menggunakan Metode Bayesian Regularization Neural Network (Rbnn).” Jurnal Informatika Universitas Padjadjaran 11(1):40.
Devy, Helln Angga, and R. B. Soemanto. 2017. “Pengembangan Obyek Dan Daya Tarik Wisata Alam Sebagai Daerah Tujuan Wisata Di Kabupaten Karanganyar (Studi Kasus Obyek Wisata Air Terjun Jumog Di Kawasan Wisata Desa Berjo, Kecamatan Ngargoyoso, Kabupaten Karanganyar).” Jurnal DILEMA Sosiologi Universitas Sebelas Maret 32(1):35.
DISBUDPAR. 2019. “Wisata Warisan Budaya Lawang Sewu.” Dinas Kebudayaan Dan Pariwisata Kota Semarang. Retrieved April 2, 2020 (http://pariwisata.semarangkota.go.id/lawang-sewu/).
Evanmartua. 2020. “Twitter COVID19 Indonesia Sentiment Analysis Lexicon Based.” GitHub. Retrieved (https://github.com/evanmartua34/TwitterCOVID19-Indonesia-Sentiment-Analysis---Lexicon-Based). Giuseppegambino. 2020. “Scraping TripAdvisor with Python 2020.” GitHub.
Retrieved March 20, 2020 (https://github.com/giuseppegambino/ScrapingTripAdvisor-with-Python-2020).
Handayani, Fitri, and Feddy Setio Pribadi. 2015. “Implementasi Algoritma Naive Bayes Classifier Dalam Pengklasifikasian Teks Otomatis Pengaduan Dan Pelaporan Masyarakat Melalui Layanan Call Center 110.” Jurnal Teknik Elektro Universitas Negeri Semarang 7(1):20.
Imron, Ali. 2019. “Analisis Sentimen Terhadap Tempat Wisata Di Kabupaten Rembang Menggunakan Metodde Naïve Bayes Classifier.” Jurnal Teknik Informatika Univaersitas Islam Indonesia.
Josi, Ahmat, Leon Andretti Abdillah, and Suryayusra. 2014. “Penerapan Teknik Web Scraping Pada Mesin Pencari Artikel Ilmiah.” Jurnal Ilmu Komputer Universitas Bina Darma. Khotimnr. 2019. “SentiStrengthID.” GitHub. Retrieved April 20, 2002 (https://github.com/khotimnr/SentiStrengthID/blob/master/Sentiment_Analysis_ (Solution).Ipynb). Mardi, Yuli. 2017. “Data Mining : Klasifikasi Menggunakan Algoritma C4.5.” Jurnal Edik Informatika STKIP PGRI Sumatera Barat 2(2):216.
Menarianti, Ika. 2015. “Klasifikasi Data Mining Dalam Menentukan Pemberian Kredit Bagi Nasabah Koperasi.” Jurnal Ilmiah Teknosains 1(1):40. Meyers, Koen. 2009. Ekowisata: Panduan Dasar Pelaksanaan. Jakarta: UNESCO Digital Library.
Mishra, Madhav. 2020. “Python Implementation of SVM, Logistics Regression, Naive Bayes, Decision Tree, Random Forest Using Scikit-Learn (Just 3 Line of Code).” Medium. RetrievedJuly 22, 2002 (https://medium.com/analyticsvidhya/python-implementation-of-svm-logistics-regression-naive-bayesdecision-tree-random-forest-1f8a5755c37b).
Purbo, Onno W. 2019. Text Mining Analisis MedSos, Kekuatan Brand & Intelejen Di Internet. edited by A. A. Christian. Yogyakarta: Andi. Rahman, M. Fadl., M. Ilha.
Ramli, Desi Yuniarti, and Rito Goejantoro. 2013. “Perbandingan Metode Klasifikasi Regresi Logistik Dengan Jaringan Saraf Tiruan (Studi Kasus: Pemilihan Jurusan Bahasa Dan IPS Pada SMAN 2 Samarinda Tahun Ajaran 2011/2012).” Jurnal EKSPONENSIAL Universitas Mulawarman 4(1):17.
Rozi, Imam Fathrur, Sholeh Hadi Pramono, and Erfan Achmad Dahlan. 2012. “Implementasi Opinion Mining (Analisis Sentimen) Untuk Ekstraksi Data Opini Publik Pada Perguruan Tinggi.” Jurnal EECCIS Universitas Brawijaya 6(1):37.
Setio, Panji Bimo Nugroho, Dewi Retno Sari Saputro, and Bowo Winarno. 2020. “Klasifikasi Dengan Pohon Keputusan Berbasis Algoritme C4.5.” Prosiding Seminar Nasional Matematika.
Setya, Mayang Vini. 2017. “Strategi Dinas Kebudayaan Dan Pariwisata Kota Semarang Dalam Upaya Mengembangkan Pariwisata Kota Semarang.” Jurnal Ilmu Pemerintahan Undip 6.
Sugiana, Owo. 2003. Membuat Aplikasi Bisnis Menggunakan Bahasa Python Dan Database Berbasis SQL. Jakarta.
Sugiyono. 2009. Metode Penelitian Pendidikan Pendekatan Kuantitatif, Kualitatif, Dan R&D. Bandung: Alfabeta.
Suryono, Sigit, Ema Utami, and Emba Taufiq Luthfi. 2018. “Klasifikasi Sentimen Pada Twitter Dengan Naive Bayes Classifier.” ANGKASA-Jurnal Ilmiah Bidang Teknologi 10(1):91.
Suyanto. 2019. Data Mining Untuk Klasifikasi Dan Klasterisasi Data. Bandung: Informatika. TripAdvisor. 2018. “TripAdvisor.” Retrieved(https://play.google.com/store/apps/details?id=com.tripadvisor.tripadvisor&hl=i n).
Vulandari, Retno Tri. 2017. Data Mining Teori Dan Aplikasi Rapidminer. Yogyakarta: Gava Media.
Yunus, Muhammad. 2020a. “Text Preprocessing Menggunakan Pandas, NLTK Dan Sastrawi Untuk Large Dataset.” Medium. Retrieved June 12, 2020
Yunus, Muhammad. 2020b. “TF-IDF (Term Frequency-Inverse Document Frequency) : Representasi Vector Data Text.” Medium. Retrieved April 17, 2020 (https://medium.com/@yunusmuhammad007/tf-idf-term-frequency-inversedocument-frequency-representasi-vector-data-text-2a4eff56cda).
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