ANALISIS SENTIMEN KEPUASAN PEMANGKU KEPENTINGAN MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER DAN K-NEAREST NEIGHBOUR

Ni Luh Ratniasih; Larasati Nabila Putri

doi:10.35959/jik.v11i02.378

Ni Luh Ratniasih Institut Teknologi dan Bisnis STIKOM Bali
Larasati Nabila Putri ITB STIKOM Bali

DOI: https://doi.org/10.35959/jik.v11i02.378

Abstract

Stakeholders are individuals or groups who have interests and can exert influence on an object. It is very important to measure the satisfaction of stakeholders (stakeholders) to get feedback and input for the purposes of developing and implementing strategies to increase stakeholder satisfaction, so it is necessary to know the opinions of stakeholders. The research method consists of several stages including the first stage is problem identification and literature study, the second stage is collecting data on stakeholder satisfaction (Students), the third stage is data preprocessing, the fourth stage is feature extraction in order to facilitate classification using the Naïve Bayes Classifier (NBC) method and K-Nearest Neighbor (KNN). The fourth stage is the testing and evaluation stage of the model. The fifth stage is testing the accuracy of the method. The purpose of this study is to compare the level of accuracy between the Naïve Bayes Classifier (NBC) and K-Nearest Neighbor (KNN) methods on sentiment analysis from comments on the results of measuring stakeholder satisfaction. The results of the accuracy rate using the Naïve Bayes Classifier (NBC) method of 91.13% and K-Nearest Neighbor (KNN) of 83.06% so that the performance of the Naïve Bayes Classifier (NBC) method is higher in the analysis of stakeholder satisfaction sentiment.

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