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All Journal KLIK: Kajian Ilmiah Informatika dan Komputer
Dimas Ferarizki
Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru
Computer Science & IT

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Klasifikasi Sentimen Masyarakat di Twitter Terhadap Ancaman Resesi Ekonomi 2023 dengan Metode K-Nearest Neighbor Dimas Ferarizki; Yusra; Muhammad Fikry; Febi Yanto; Fitri Insani
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 2 (2023): Oktober 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i2.1306

Abstract

A recession is a decline in overall economic activity, this is considered a phase of significant and sustainable economic decline in various sectors and economic indicators. The threat of a recession in 2023 has become a topic of discussion in many countries, including Indonesia. This happens because Indonesia is threatened as a country affected by a recession due to weakening economic activity in the real sector. This sentiment classification research aims to analyze public opinion and opinion regarding the issue of recession news in 2023 which is conveyed via the social media platform Twitter. This research aims to understand whether these opinions fall into the category of positive sentiment or negative sentiment. Apart from that, this research also aims to measure the level of accuracy in classifying these sentiments into appropriate classes. This research has several main processes starting from data collection then manual data labeling, text processing, feature weighting (TF-IDF), Thresholding feature selection and K-Nearest Neighbor method classification. Based on the classification results using a testing model from a total of 1000 comment data divided between 596 positive class data and 404 negative class Twitter data regarding the threat of recession in 2023, the highest accuracy results were obtained at 85% at a value of k = 3 using the 90:10 comparison model training and testing data
Co-Authors Febi Yanto Fitri Insani Muhammad Fikry Yusra