Analisis Sentimen Opini Mahasiswa Terhadap Saran Kuesioner Penilaian Kinerja Dosen dengan Menggunakan TF-IDF dan K-Nearest Neighbor - Nur Shafiya Nabilah Salam; Ahmad Afif Supianto; Andi Reza Perdanakusuma (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2019)
Faculty of Computer Science on the University of Brawijaya evaluates lecturer performance every semester and the evaluation program was carried out by the Quality Assurance Unit (UJM) Team. UJM Team does the evaluation by distributing questionnare within the Student Academic Information System (SIAM). There were two section on the questionnaire, multiple choice section and the comment section. After collecting data, UJM Team processed the data from the comment section manually. The comment section contained student's perspective of the lecturer performance, which has never been processed to date to be used as an evaluation material. Therefore, this study is performed to assist UJM Team to process the data from the comment section using Sentiment Analysis on sentence level with K-Nearest Neighbor classification method. Out of 2210 opinion data from students of the Information Technology Study Program analyzed from three semester period in the Even Semester 2016/2017, Odd Semester 2017/2018, and Even Semester 2017/2018, the classification result in an average accuracy of 81%. The result of this study is a list of opinions and bar chart showing the frequency of opinions that have been classified and will be displayed as a dashboard. This data opinions can also be filterred by lecturer's subjects and his/her name.