Jurnal Linguistik Komputasional
Vol 7 No 1 (2024): Vol. 7, NO. 1

Analisis Sentimen dan Topik Perbincangan Netizen Indonesia Terkait Pengurangan Subsidi BBM

Mulia, Adi (Unknown)
Dzikrillah, Akhmad Rizal (Unknown)



Article Info

Publish Date
26 Mar 2024

Abstract

Abstract- This research was conducted with the aim that is based on problems that arise in society, namely the increase in fuel prices. The sentiment classification method applied by researchers is to use a lexicon corpus dictionary that takes into account positive and negative sentiment values. The researcher then compares the sentiment between before and after the fuel price increase policy. Furthermore, the researcher applied Latent Dirichlet Allocation or (LDA) topic modeling to find out whether the discussion of the fuel price increase became the main topic when the fuel rose. The results of this study show that after announcing the fuel price increase in September 2022, the percentage of negative tweets directed at President Jokowi has increased when compared to before announcing the fuel price increase. The percentage of positive tweets directed at President Jokowi decreased when compared to before raising fuel prices. In the month when President Jokowi announced the fuel price increase policy, namely in September 2022, the topic of conversation related to the fuel price increase policy was the most popular topic of conversation in tweets directed at President Jokowi. 33.8% of tweets that discussed the fuel price increase were negative tweets with the most popular topics of discussion for netizens with negative sentiments were topics related to criticism of the Jokowi administration.

Copyrights © 2024






Journal Info

Abbrev

jlk

Publisher

Subject

Computer Science & IT

Description

Jurnal Linguistik Komputasional (JLK) menerbitkan makalah orisinil di bidang lingustik komputasional yang mencakup, namun tidak terbatas pada : Phonology, Morphology, Chunking/Shallow Parsing, Parsing/Grammatical Formalisms, Semantic Processing, Lexical Semantics, Ontology, Linguistic Resources, ...