Jupiter
Vol 14 No 2-a (2022): Jupiter Edisi Oktober 2022

Klasifikasi Pertanyaan Berbahasa Indonesia Menggunakan Algoritma Support Vector Machine dan Seleksi Fitur Mutual Information

syechky al qodrin aruda (Universitas Sriwijaya)
Novi Yusliani (Universitas Sriwijaya)
Alvi Syahrini (Universitas Sriwijaya)

Article Info

Publish Date
26 Oct 2022

Abstract

Text classification can be used to organize, arrange and categorize a text. Text classification can be used for all text documents even if a text has a large number of features. However, the large number of features can cause reduced accuracy in the performance results of the classification system because there are some features that have less relevance to a text category. The Mutual Information feature selection method combined with the Support Vector Machine (SVM) algorithm is used to improve performance results in the classification process for Indonesian question documents by eliminating features with weights below the threshold. The results showed that the use of the Mutual Information feature selection method on the SVM classification algorithm was able to produce the best performance with an accuracy value of 0.92, precision: 0.93, recall: 0.89, f-measure: 0.9, computation time: 7 s and number of features: 240. Keywords— Text Classification, Feature Selection, Support Vector Machine, Mutual Information

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Journal Info
Jupiter
Website

Abbrev

jupiter

Publisher

Politeknik Negeri Sriwijaya

Subject

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering Library & Information Science

Description

Tentang Jurnal Ini Fokus dan Ruang Lingkup Bidang kajian yang dapat dimuat pada jurnal Jupiter meliputi dan tidak terbatas pada: Mobile Computing Image Processing Computer Graphic Artificial Intelligence Information Retrieval Computer Vision Algorithm & Complexity Data Mining Information System ...