Indonesian Journal on Data Science
Vol 1 No 1 (2023): Indonesian Journal on Data Science

Sentiment Analysis Related National Social Security Agency for Employment in Indonesia: Hybrid Method Using Lexicon Based and Naive Bayes Classifier Approaches

Rizky Fauzi Akbar (Universitas Jenderal Achmad Yani Yogyakarta)
Muhammad Habibi (Universitas Jenderal Achmad Yani Yogyakarta)



Article Info

Publish Date
11 May 2023

Abstract

The National Social Security Agency (BPJS) for Employment is the Social Security Administering Agency with the goal of ensuring that each participant or member of the family receives adequate necessities. In its implementation, there is information that is spread, particularly on Twitter, regarding the Ministry of Health's decision, namely regarding Old Age Security (JHT), which can only be distributed/taken after the participant turns 56 years old, causing both pros and cons among the public. Based on unanalyzed tweets on Twitter, it is necessary to do extensive research to collect relevant information based on netizens' viewpoints. This research describes sentiment analysis of tweets from Twitter using the terms JHT, BPJSTK, and BPJS, which yield 4154 data tweets. We employ two approaches in this study: Lexicon Based and Nave Bayes Classifier. According to this study, the accuracy of the testing data is 92% for the Lexicon Based and 95% for the Nave Bayes Classifier. This study concluded that the JHT at BPJS Employment received unfavorable attitudes and negative reactions among users who addressed the rejection of new restrictions where JHT, could only be dispensed or taken when participants at BPJS Employment were 56 years old.

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Journal Info

Abbrev

ijds

Publisher

Subject

Computer Science & IT

Description

Indonesian Journal of Data Science (IJDS) adalah Jurnal ilmiah yang memuat hasil penelitian pada ranah data science (Ilmu Data). Cangkupan jurnal meliputi: 1. Big Data 2. Machine Learning 3. Data Mining 4. Deep Learning 5. Artificial ...