Analisa Sentimen Pada Media Sosial“X” Pencarian Keyword ChatGPT Menggunakan Algoritma K-Nearest Neighbors (KNN)

Sentiment analysis of the use of Artificial Intelligence (AI) is becoming increasingly important in public understanding of today's rapidly evolving technology, as it helps facilitate human activities. One of the key applications is the presence of ChatGPT, an AI capable of interacting with users through user input, such as answering various questions posed. This topic generates a lot of pros and cons, as widely discussed on social media. Research is needed to evaluate how wisely people use this AI. This study proposes an approach using the K-Nearest Neighbors (KNN) algorithm to analyze AI-related sentiment. The KNN algorithm is used to classify sentiment into positive, negative, or neutral, based on the similarity with the closest word in the feature space derived from text data. This method allows for efficient sentiment grouping without the need for complex models. Researchers chose sentiment analysis because it is an appropriate technique for data processing. Of the 1000 reviews collected from social media users on “X,” 853 were positive, and 147 were negative. The data was classified using the KNN algorithm, followed by an accuracy evaluation yielding 84.80%. The results of this sentiment analysis are expected to guide decision-makers in developing and applying AI technology more intelligently, in line with societal needs and expectations.

Authors

Publication Details

Journal
Jurnal Indonesia Manajemen Informatika dan Komunikasi
Published
2024-09-19
DOI
https://doi.org/10.35870/jimik.v5i3.1016
Citations
2
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
1.56
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article

Analisa Sentimen Pada Media Sosial“X” Pencarian Keyword ChatGPT Menggunakan Algoritma K-Nearest Neighbors (KNN)

Tri Wahyudi, Sugiyono Sugiyono, Anggit Nur Hannaa Regita, Yuma Akbar
2 citations
Jurnal Indonesia Manajemen Informatika dan Komunikasi
Data Mining and Machine Learning Applications
1.56
article

Analisa Sentimen Pada Media Sosial“X” Pencarian Keyword ChatGPT Menggunakan Algoritma K-Nearest Neighbors (KNN)

Tri Wahyudi, Sugiyono Sugiyono, Anggit Nur Hannaa Regita, Yuma Akbar
article en
2 citations

Abstract

Sentiment analysis of the use of Artificial Intelligence (AI) is becoming increasingly important in public understanding of today's rapidly evolving technology, as it helps facilitate human activities. One of the key applications is the presence of ChatGPT, an AI capable of interacting with users through user input, such as answering various questions posed. This topic generates a lot of pros and cons, as widely discussed on social media. Research is needed to evaluate how wisely people use this AI. This study proposes an approach using the K-Nearest Neighbors (KNN) algorithm to analyze AI-related sentiment. The KNN algorithm is used to classify sentiment into positive, negative, or neutral, based on the similarity with the closest word in the feature space derived from text data. This method allows for efficient sentiment grouping without the need for complex models. Researchers chose sentiment analysis because it is an appropriate technique for data processing. Of the 1000 reviews collected from social media users on “X,” 853 were positive, and 147 were negative. The data was classified using the KNN algorithm, followed by an accuracy evaluation yielding 84.80%. The results of this sentiment analysis are expected to guide decision-makers in developing and applying AI technology more intelligently, in line with societal needs and expectations.

Jurnal Indonesia Manajemen Informatika dan KomunikasiVol. 5(3)
Openalex Percentile: Top 13%
Data Mining and Machine Learning Applications
1.56
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