Analisa Sentimen Masyarakat Naiknya Bahan Pokok Menggunakan Algoritma Teks Mining Dan TF-IDF

Weno Syechu

doi:10.47065/jussi.v4i2.7802

Weno Syechu * Politeknik Negeri Medan, Medan, Indonesia

(*) Corresponding Author

DOI: https://doi.org/10.47065/jussi.v4i2.7802

Keywords: Increase in Basic Materials; Text Mining; TF-IDF

Abstract

Twitter is one of the social media used by the public to express opinions on news that is often discussed. Various opinions were expressed by the public on Twitter social media, including expressing opinions and complaints regarding the increase in basic commodities. Staples are people's basic needs in everyday life. Rising prices of basic commodities are a problem that society often faces. Therefore, the government must take steps to reduce the increase in prices of basic commodities, such as strengthening market control and regulation, increasing agricultural production, and providing subsidies to people who cannot afford it. This research aims to measure public sentiment regarding the increase in basic commodities for the community and it is hoped that it can become a benchmark for government parties related to the increase in basic commodities, so that it does not affect inflation and the stability of the community's economy. This research was carried out by taking 100 data from Twitter using crawling techniques and processing 50 data using TF-IDF weighting. Then the data was processed using text mining and a word weighted search was carried out using the Term Frequency Inverse Document Frequency (TF-IDF) algorithm. The results of this research showed that the percentage of public sentiment towards the increase in basic commodities with positive sentiment was 24.2414% and negative was 75.7586%.

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