ANALISIS SENTIMEN PELAYANAN BPJS MENGGUNAKAN ALGORITMA NAIVE BAYES DAN PARTICLE SWARM OPTIMIZATION

MUHAMMAD, SYAUGI AFIF and Kurniati, Rizki and Arsalan, Osvari (2023) ANALISIS SENTIMEN PELAYANAN BPJS MENGGUNAKAN ALGORITMA NAIVE BAYES DAN PARTICLE SWARM OPTIMIZATION. Undergraduate thesis, Sriwijaya University.

	Text RAMA_55201_ 09021381924129.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (2MB) | Request a copy
	Text RAMA_55201_ 09021381924129_TURNITIN.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (9MB) | Request a copy
	Text RAMA_55201_ 09021381924129_ 0012079104_ 0028068806_01_front_ref.pdf - Accepted Version Available under License Creative Commons Public Domain Dedication. Download (676kB)
	Text RAMA_55201_ 09021381924129_ 0012079104_ 0028068806_02.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (256kB) | Request a copy
	Text RAMA_55201_ 09021381924129_ 0012079104_ 0028068806_03.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (231kB) | Request a copy
	Text RAMA_55201_ 09021381924129_ 0012079104_ 0028068806_04.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (1MB) | Request a copy
	Text RAMA_55201_ 09021381924129_ 0012079104_ 0028068806_05.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (229kB) | Request a copy
	Text RAMA_55201_ 09021381924129_ 0012079104_ 0028068806_06.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (7kB) | Request a copy
	Text RAMA_55201_ 09021381924129_ 0012079104_ 0028068806_07_ref.pdf - Bibliography Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (201kB) | Request a copy

Abstract

BPJS is a legal entity aimed at providing healthcare coverage to the public. However, the increasing number of people using BPJS services has generated both support and opposition among the community. This research aims to analyze public opinions regarding the Social Security Administration Agency (BPJS) on Twitter. The method employed in this study is the Naïve Bayes Classifier with Particle Swarm Optimization (PSO) as the feature selection method. In this research, the PSO feature selection parameters are set with 40 particles, a cognitive coefficient (c1) of 1.2, a social coefficient (c2) of 0.6, and an inertia (w) of 0.1. The evaluation is conducted by comparing the Naïve Bayes method without feature selection and the Naïve Bayes method with PSO feature selection. The results indicate that the Naïve Bayes method without feature selection successfully classifies text with an accuracy of 79.1%. However, with the implementation of PSO feature selection, the classification accuracy increases to 92.2%. This demonstrates that utilizing PSO feature selection with properly set parameters improves the accuracy by 13.1%. This research providesa better understanding of public sentiment towards BPJS services and highlights the effectiveness of Naïve Bayes classification when combined with PSO feature selection in classifying public opinions related to BPJS services. Keywords: BPJS, Feature Selection, Naïve Bayes Classifier, Particle Swarm Optimization (PSO), Sentiment analysis

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Analisis Sentimen,BPJS, Naïve Bayes Classifier, Particle Swarm Optimization,Seleksi fitur Analisis Sentimen,BPJS, Naïve Bayes Classifier, Particle Swarm Optimization,Seleksi fitur Analisis Sentimen,BPJS, Naïve Bayes Classifier, Particle Swarm Optimization,Seleksi fitur
Subjects:	T Technology > T Technology (General) > T58.5-58.64 Information technology > T58.5 General works Management information systems Cf. HD30.213 Industrial management Cf. HF5549.5.C6+ Communication in personnel management Cf. TS158.6 Automatic data collection systems (Production control)
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Muhammad Syaugi Afif
Date Deposited:	02 Aug 2023 07:24
Last Modified:	02 Aug 2023 07:24
URI:	http://repository.unsri.ac.id/id/eprint/125198

Actions (login required)

View Item