Klasifikasi Sentiment Analysis pada Saran Pelayanan dan Fasilitas Perpustakaan Politeknik Caltex Riau menggunakan Algoritma K-Nearest Neighbor

Abstract

The libraries will annually evaluate the services and facilities provided during the year by giving the questionnaire. The questionnaire contains a statement of advice is feedback given to the students of PCR library services and facilities. The data is useful to classify the student suggestions into sentiment analysis. Data advice given student must have a number of lots that require time for processing. He built a system that can help the library to process data from student suggestions are Classification Sentiment Analysis in Saran Library Services and Facilities PCR with k-Nearest Neighbor algorithm so that the libraries can be to determine the classification of the advice of students to the library. From this study, the classification of suggestions using the k-Nearest Neighbor algorithm obtained prediction accuracy of 85% with a value of k 3.