IMPLEMENTATION OF K-NEAREST NEIGHBOR ALGORITHM FOR SENTIMENT ANALYSIS CASE STUDY : ANGKET EVALUASI PERKULIAHAN (AEP)

KURNIAWAN, YUNIAR AGUNG (2018) IMPLEMENTATION OF K-NEAREST NEIGHBOR ALGORITHM FOR SENTIMENT ANALYSIS CASE STUDY : ANGKET EVALUASI PERKULIAHAN (AEP). Other thesis, Unika Soegijapranata Semarang.

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Abstract

ABSTRACT The questionnaire is one of the most commonly used data or data collection techniques in lectures. Questionnaire Evaluation Lecture (AEP) is used to determine the results of student evaluation of the lecture system experienced in a semester of lectures. Unfortunately to determine which questionnaire has a positive response or a negative response can not be determined automatically. To assist lecturers in determining the responses contained in the questionnaire, for that project was created. The project uses the K-Nearest Neighbor algorithm to classify questionnaire opinions based on similarities between documents. This project will determine the opinions contained in the questionnaire and classify the questionnaire with positive and negative opinions Keywords: K-Nearest Neighbour, Sentiment Analysis, Cosine Similarity

Item Type: Thesis (Other)
Subjects: 000 Computer Science, Information and General Works > 005 Computer programming, programs & data > Information Systems
Divisions: Faculty of Computer Science > Department of Informatics Engineering
Depositing User: Mr Lucius Oentoeng
Date Deposited: 21 Jun 2018 04:10
Last Modified: 23 Feb 2021 07:55
URI: http://repository.unika.ac.id/id/eprint/16118

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