Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : JITK (Jurnal Ilmu Pengetahuan dan Komputer)

A SYSTEMATIC LITERATURE REVIEW: RECURSIVE FEATURE ELIMINATION ALGORITHMS Arif Mudi Priyatno; Triyanna Widiyaningtyas
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 9 No. 2 (2024): JITK Issue February 2024
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v9i2.5015

Abstract

Recursive feature elimination (RFE) is a feature selection algorithm that works by gradually eliminating unimportant features. RFE has become a popular method for feature selection in various machine learning applications, such as classification and prediction. However, there is no systematic literature review (SLR) that discusses recursive feature elimination algorithms. This article conducts a SLR on RFE algorithms. The goal is to provide an overview of the current state of the RFE algorithm. This SLR uses IEEE Xplore, ScienceDirect, Springer, and Scopus (publish and publish) databases from 2018 to 2023. This SLR received 76 relevant papers with 49% standard RFEs, 43% strategy RFEs, and 8% modified RFEs. Research using RFE continues to increase every year, from 2018 to 2023. The feature selection method used simultaneously or for comparison is based on a filter approach, namely Pearson correlation, and an embedded approach, namely random forest. The most widely used machine learning algorithms are support vector machines and random forests, with 19.5% and 16.7%, respectively. Strategy RFE and modified RFE can be referred to as hybrid RFEs. Based on relevant papers, it is found that the RFE strategy is broadly divided into two categories: using RFE after other feature selection methods and using RFE simultaneously with other methods. Modification of the RFE is done by modifying the flow of the RFE. The modification process is divided into two categories: before the process of calculating the smallest weight criteria and after calculating the smallest weight criteria. Calculating the smallest weight criteria in this RFE modification is still a challenge at this time to obtain optimal results.
Co-Authors - Ardiansyah, - Abdul Hadi, Afif Adam Ramadhani P Adiba Qonita Ahmad Farobi Ahmad Fuadi Aji P Wibawa Aji Prasetya Wibawa Ali, Waleed Annas Gading Pertiwi Arif Mudi Priyatno Aya Shofia Mufti Bambang Nurdewanto Bintang Romadhon Binti Afifah Brilliant, Muhammad Zidan Budi Wibowotomo Darwis, Herdianti Dasuki, Moh. Didik Dwi Prasetya Ega Gefrie Febriawan Elta Sonalitha Fadhlullah, Aufar Faiq Fadli Hidayat, M. Noer Falah, Moh Zainul Fitriyah Fitriyah Fitriyah Fitriyah Gading Pertiwi, Annas Gamma Fitrian Permadi Hairani Hairani Haviluddin Haviluddin Hazizah, Chalista Yulia Heru Wahyu Herwanto I Made Wirawan Imansyah, Pranadya Bagus Indriana, Poppy Kornelius Kamargo/Irawan Dwi Wahyono Kornelius Kamargo Kurniawan, Mohamad Yusuf Kurniawan, Rizky Rizaldi M. Ardhika Mulya Pratama M. Zainal Arifin Martin Indra Wisnu Prabowo Maryani, Sri Moh Zainul Falah Muhammad Afnan Habibi Muhammad Firman Aji Saputra Muhammad Iqbal Akbar Muhammad Jauharul Fuady Muhammad Rizki Irwanto Mulki Indana Zulfa, Mulki Indana Mulya Pratama, M. Ardhika Nafalski, Andrew Nurhidayati Pindo Tutuko Poppy Indriana Pratama, Satria Putra Purnawansyah Purnawansyah Qonita, Adiba Raja, Roesman Ridwan Rendy Yani Susanto Rhomdani, Rohmad Wahid Rizal, Muhammad Fatkhur Rosydah, Lucyta Qutsyaning Saifudin, Ilham Setiadi Cahyono Putro Shandy Krisnawan Soenar Soekopitojo Soraya Norma Mustika Sucipto Sucipto Sucipto Sucipto Sujito Sujito Syaad Patmanthara Syah, Abdullah Iskandar Syamsul Arifin Utomo Pujianto Wahyu Caesarendra Wahyu Sakti Gunawan Wahyu Sakti Gunawan Irianto Wibawa, Aji P Wisnu Prabowo, Martin Indra Yogi Dwi Mahandi Yuniardini, Fatma