Analisis Sentimen Terhadap Data Kuisioner Evaluasi Dosen Menggunakan Algoritma Naïve Bayes

Abstract

Students' satisfaction with the quality of lecturers' way of teaching is oneof theimportant things in higher education institutions. Universitas Ichsan Gorontalo hasimplemented an online questionnaire as student feedback to determine and evaluatethe performance of lecturers. The Faculty of Computer Science is one of the facultiesthathasimplementedthequestionnairefillingsystem.Thequestionnaireismandatoryfor all students as a requirement to join a course contract at the beginning of thesemester. The evaluation of the performance of lecturers during lectures has a veryimportantrole.Itimprovesthequalityoflearningandacademicstandardization.Thisstudy aims to determine the level of student satisfaction with the services of lecturerswhen teaching. This study applies sentiment analysis using the Naïve Bayes Classifierclassificationmethod.ItalsoemploystheweightingmethodusingtheTermFrequency-Inverse Document Frequency (TF-IDF). The results of this study have determined theclassification of the lecturer service questionnaire data. The results are easy to read.Theresultsofthesurveyonthelevelofstudentsatisfactionwithlecturerservicesfrom1,989dataindicatethat1,946datahavepositivesentimentsand43datahavenegativesentiments.TheresultsgainedfromtheNaïve Bayesaccuracy is 97%accuracy.