Analisis Sentimen Terhadap Sistem Informasi Akademik Mahasiswa pada Aplikasi Edlink dengan Metode K-Nearest Neighbor

The Sevima Edlink application is an academic information system that is widely used by educational institutions in Indonesia to manage student academic data and information. Although this application has various useful features, its successful implementation also depends greatly on user satisfaction and acceptance. Therefore, it is important to analyze user sentiment towards these applications to identify existing strengths and weaknesses. This research aims to analyze user sentiment towards the Sevima Edlink application using the K-Nearest Neighbor (K-NN) method. The K-NN method was chosen because of its simplicity and effective ability to classify sentiment data. The data used in this research are reviews from application users collected from various sources. The results of this research used the K-NN method, namely an accuracy value of 94.47%. So it can be said that the K-KNN algorithm can classify data well and correctly.

Authors

Publication Details

Journal
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi)
Published
2024-11-10
DOI
https://doi.org/10.35870/jtik.v9i1.3017
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Analisis Sentimen Terhadap Sistem Informasi Akademik Mahasiswa pada Aplikasi Edlink dengan Metode K-Nearest Neighbor

Citra Pricylia Ananda Mulya, Veri Arinal
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi)
Data Mining and Machine Learning Applications
article

Analisis Sentimen Terhadap Sistem Informasi Akademik Mahasiswa pada Aplikasi Edlink dengan Metode K-Nearest Neighbor

Citra Pricylia Ananda Mulya, Veri Arinal
article en

Abstract

The Sevima Edlink application is an academic information system that is widely used by educational institutions in Indonesia to manage student academic data and information. Although this application has various useful features, its successful implementation also depends greatly on user satisfaction and acceptance. Therefore, it is important to analyze user sentiment towards these applications to identify existing strengths and weaknesses. This research aims to analyze user sentiment towards the Sevima Edlink application using the K-Nearest Neighbor (K-NN) method. The K-NN method was chosen because of its simplicity and effective ability to classify sentiment data. The data used in this research are reviews from application users collected from various sources. The results of this research used the K-NN method, namely an accuracy value of 94.47%. So it can be said that the K-KNN algorithm can classify data well and correctly.

Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi)Vol. 9(1)
Openalex Percentile: Top 67%
Data Mining and Machine Learning Applications
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