Analisis Komentar Hasil Belajar Siswa Menggunakan Opinion Summarization
The quality of a teacher has become the center of attention in research in the field of education. The quality of the teacher is not only measured by the qualifications and insights of a teacher, but also dedication and commitment in the classroom One of the things that can be used to assess the quality of teachers is to assess the opinions of students. Therefore, student opinions at the end of the class such as questionnaires are needed to help teachers understand student learning behavior and improve the quality of teaching in the classroom. Opinion summarization is a method to make summaries automatically from a set of opinions about a particular target. Opinion summarization will explore the features of one's opinion, capture whether the opinion includes positive or negative opinions, then summarize the results. Based on the results of testing and analysis that has been done in the previous discussion, it can be concluded that the accuracy value obtained is 93,44% with 97,66% precision and 92,85%. recall. This proves that the system that has been built is accurate and can help the company to see the performance of the teachers.
 Bjørkelund Eivind, Burnett Thomas H. and Nørvåg Kjetil A study of opinion mining and visualization of hotel reviews [Conference] // Proceedings of the 14th International Conference on Information Integration and Web-based Applications & Services - IIWAS '12. - 2012. - 10.1145/2428736.2428773.
 Chaowalit Orawan Abstractive Thai Opinion Summarization Title of Dissertation Abstractive Thai Opinion Summarization [Journal].
 HaCohen-Kerner Yaakov and Badash Haim Positive and Negative Sentiment Words in a Blog Corpus Written in Hebrew [Conference] // Procedia Computer Science. - 2016. - 10.1016/j.procs.2016.08.257.
 He Wu, Zha Shenghua and Li Ling Social media competitive analysis and text mining: A case study in the pizza industry [Journal] // International Journal of Information Management. - 2013. - 10.1016/j.ijinfomgt.2013.01.001.
 Hendy Evan Fabianus and Sigit Purnomo Y WP Pembangunan Perangkat Lunak Peringkas Dokumen dari Banyak Sumber Menggunakan Sentence Scoring dengan Metode TF-IDF [Journal] // Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Yogyakarta. - 2014. - 17 : Vol. 21. - pp. 1907-5022.
 Hu Minqing and Liu Bing Mining and summarizing customer reviews [Conference] // Proceedings of the 2004 ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '04. - 2004. - 10.1145/1014052.1014073.
 Kaewyong Phuripoj [et al.] The Possibility of Students Comments Automatic Interpret Using Lexicon Based Sentiment Analysis to Teacher Evaluation [Journal]. - 2015. - pp. 12-13.
 Kamal Ahmad Review Mining for Feature Based Opinion Summarization and Visualization [Journal].
 Karnik, A. “Performance of TCP congestion control with rate feedback:TCP/ABR and rate adaptive TCP/IP,” M. Eng. thesis, Indian Institute ofScience, Bangalore, India, Jan. 1999.
 Kaur Amandeep and Gupta Vishal A survey on sentiment analysis and opinion mining techniques // Journal of Emerging Technologies in Web Intelligence. - 2013. - 10.4304/jetwi.5.4.367-371..
 Leong Chee Kian, Lee Yew Haur and Mak Wai Keong Mining sentiments in SMS texts for teaching evaluation [Journal] // Expert Systems with Applications. - 2012. - 10.1016/j.eswa.2011.08.113.
 López Condori Roque Enrique and Salgueiro Pardo Thiago Alexandre Opinion summarization methods: Comparing and extending extractive and abstractive approaches [Journal] // Expert Systems with Applications. - 2017. - 10.1016/j.eswa.2017.02.006.
 Rajput Quratulain, Haider Sajjad and Ghani Sayeed Lexicon-Based Sentiment Analysis of Teachers' Evaluation [Journal]. - 10.1155/2016/2385429.
 Rozi Imam Fahrur Imam Fahrur R, Implementasi Rule-Based Document [Report]. - pp. 29-41.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License