Abstract
The needs of the community for freight forwarding are now starting to increase with the marketplace. User opinion about freight forwarding services is currently carried out by the public through many things one of them is social media Twitter. By sentiment analysis, the tendency of an opinion will be able to be seen whether it has a positive or negative tendency. The methods that can be applied to sentiment analysis are the Naive Bayes Algorithm and Support Vector Machine (SVM). This research will implement the two algorithms that are optimized using the PSO algorithms in sentiment analysis. Testing will be done by setting parameters on the PSO in each classifier algorithm. The results of the research that have been done can produce an increase in the accreditation of 15.11% on the optimization of the PSO-based Naive Bayes algorithm. Improved accuracy on the PSO-based SVM algorithm worth 1.74% in the sigmoid kernel.
Highlights
The needs of the community for freight forwarding are now starting to increase with the marketplace
The methods that can be applied to sentiment analysis are the
Testing will be done by setting parameters on the Particle Swarm Optimization (PSO)
Summary
Analisis sentimen mampu mengubah teks secara otomatis untuk dapat mengestrak sentimen pada sebuah kalimat. Opini pengguna tentang pelayanan ekspedisi barang Naive Bayes, dimana metode tersebut akan mampu saat ini dilakukan masyarakat melalui banyak media melihat peluang dari setiap kondisi [7]. Alur metode yang akan mampu menghasilkan tingkat akurasi tertinggi senilai dilakukan terdapat pada Gambar 1. Diagram Alur Penelitian pengujian yang dilakukan didapatkan bahwa penerapan Pada penerapan Algoritma Naive Bayes berbasis PSO PSO dapat meningkatkan akurasi sebesar 6.42% [13]. Pada penerapan Algoritma Support Vector dilakukan sebuah komparasi Algoritma classifier Machine pengujian akan diawali dengan pemilihan Support Vector Machine dan Naive Bayes berbasis kernel dengan hasil terbaik. Penerapan Metode diawali dengan operator Search Twitter , pada tahap ini ditentukan jumlah data yang akan diambil dan query. Operator Analyze Sentimen merupakan proses yang akan mengklasifikasikan data menjadi kategori opini positif dan negatif. Data yang sudah diambil akan dibentuk dengan format .xls seusai dengan operator Write Excell yang sudah dipilih
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
