Procedia of Social Sciences and Humanities
Vol. 3 (2022): Proceedings of the 1st SENARA 2022

Comparison of the Performance of Machine Learning Algorithms for Sarcasm Detection in Bahasa: Perbandingan Kinerja Algoritma Machine Learning Untuk Mendeteksi Kalimat Sarkasme Dalam Bahasa Indonesia

Mochamad Alfan Rosid (Universitas Muhammadiyah Sidoarjo)
Fajar Muharram (Universitas Muhammadiyah Sidoarjo)
Ghozali Rusyid Affandi (Universitas Muhammadiyah Sidoarjo)

Article Info

Publish Date
18 Jul 2022

Abstract

Twitter has become a widely used social media. The amount of data held has led to research such as sentiment analysis. Sentiment analysis has a problem when there are sarcasm sentences, the polarity of the sentiment that should be negative, becomes positive sentiment due to the use of sarcasm sentences. The purpose of this study is to compare the performance of three machine learning methods, namely Support Vector Machine, Randome Forest, and K-Nearest Neighbor to detect sarcasm sentences on Twitter social media. These three methods were chosen because they have a good performance in text classification. The dataset used is taken from Indonesian language twitter with crawling technique. From the results of the study, it was found that the Support Vector Machine method had the best performance with a recall value of 0.97, precision 0.98 and f1-score 0.98.

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Journal Info
Procedia of Social Sciences and Humanities
Website

Abbrev

pssh

Publisher

Universitas Muhammadiyah Sidoarjo

Subject

Humanities Computer Science & IT Decision Sciences, Operations Research & Management Social Sciences

Description

PSSH is a peer-reviewed international journal. This statement clarifies ethical behaviour of all parties involved in the act of publishing an article in this journal, including the author, the chief editor, the Editorial Board, the peer-reviewer­­­­­ and the publisher (Universitas Muhammadiyah ...