Optimasi Algoritma Support Vector Machine Berbasis Kernel Radial Basis Function (RBF) Menggunakan Metode Particle Swarm Optimization Untuk Analisis Sentimen
Di era digital, aplikasi Financial Technology (Fintech) telah menjadi bagian penting dalam kehidupan sehari-hari masyarakat. Kemudahan dan efisiensi yang ditawarkan oleh aplikasi Fintech menarik jutaan pengguna, yang aktif memberikan umpan balik dan ulasan di platform seperti Google Play Store. Ula...
Saved in:
| Main Authors: | Cucun Very Angkoso, Khozainul Asror, Ari Kusumaningsih, Andi Kurniawan Nugroho |
|---|---|
| Format: | Article |
| Language: | Indonesian |
| Published: |
University of Brawijaya
2025-06-01
|
| Series: | Jurnal Teknologi Informasi dan Ilmu Komputer |
| Subjects: | |
| Online Access: | https://jtiik.ub.ac.id/index.php/jtiik/article/view/9317 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
APPLICATION OF THE TEXTUAL INFORMATION ANALYSIS METHOD FOR THE PROBLEM OF CLASSIFICATION OF SCIENTIFIC ARTICLE
by: N. O. Ukhanov, et al.
Published: (2022-08-01) -
Beyond buzzwords: NLP reveals common threads in sustainable and circular construction discourse
by: Shakarim Aubakirov, et al.
Published: (2025-07-01) -
NLP based text classification using TF-IDF enabled fine-tuned long short-term memory: An empirical analysis
by: Pratiyush Guleria, et al.
Published: (2025-09-01) -
Sentiment Analysis of User Reviews of the KitaLulus Application on Google Play Store using the Support Vector Machine (SVM) Algorithm
by: Ahmad Syaifudin Agil Rafsanjani, et al.
Published: (2025-09-01) -
Computing Lightning-Induced Voltages on Overhead Distribution Lines Using the RBF-FDTD Approach
by: Duc-Quang Vu, et al.
Published: (2025-01-01)