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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Epsilon: Jurnal Matematika Murni dan Terapan Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Teknologi Informasi dan Ilmu Komputer Telematika KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Komputasi Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Sains dan Informatika Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Pengabdian Kepada Masyarakat (Mediteg) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Teknik Informatika (JUTIF) JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Pengabdian Ilung (Inovasi Lahan Basah Unggul) Journal of Data Science and Software Engineering Jurnal Teknik Ilmu dan Aplikasi Jurnal Informatika Polinema (JIP) Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics
Saragih, Triando Hamonangan
Universitas Lambung Mangkurat
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Journal : IJCCS (Indonesian Journal of Computing and Cybernetics Systems)

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Backward Elimination for Feature Selection on Breast Cancer Classification Using Logistic Regression and Support Vector Machine Algorithms Salsha Farahdiba; Dwi Kartini; Radityo Adi Nugroho; Rudy Herteno; Triando Hamonangan Saragih
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 17, No 4 (2023): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.88926

Abstract

Breast cancer is a prevalent form of cancer that afflicts women across all nations globally. One of the ways that can be done as a prevention to reduce elevated fatality due to breast cancer is with a detection system that can determine whether a cancer is benign or malignant. Logistic Regression and Support Vector Machine (SVM) classification algorithms are often used to detect this disease, but the use of these two algorithms often doesn’t give optimal results when applied to datasets that have many features, so additional algorithm is needed to improve classification performance by using Backward Elimination feature selection. The comparison of Logistic Regression and SVM algorithms was carried out by applying feature selection to breast cancer data to see the best model. The breast cancer dataset has 30 features and two classes, Benign and Malignant. Backward Elimination has reduced features from 30 features to 13 features, thereby increasing the performance of both classification models. The best classification was obtained by using the Backward Elimination feature selection and linear kernel SVM with an increase in accuracy value from 96.14% to 97.02%, precision from 98.06% to 99.49%, recall from 90.48% to 92.38%, and the AUC from 0.95 to 0.96.
Co-Authors AA Sudharmawan, AA Abadi, Friska Abdul Latief Abadi Abdullayev, Vugar Achmad Rizal Adawiyah, Laila Afifa, Ridha Ahmad Rusadi Arrahimi - Universitas Lambung Mangkurat) Ahmad Rusadi Arrahimi - Universitas Lambung Mangkurat) Ahmad Tajali Aida, Nor Ajwa Helisa Al Ghifari, Muhammad Akmal Alamudin, Muhammad Faiq Alfita Rakhmandasari Amelia Aditya Santika Andi Farmadi Andi Farmadi Anshari, Muhammad Ridha Anshory, Muhammad Naufal Ansyari, Muhammad Ridho Athavale, Vijay Anant Athavale, Vijay Annant Bachtiar, Adam Mukharil Bachtiar, Adam Mukharil Difa Fitria Dina Arifah Diny Melsye Nurul Fajri Diny Melsye Nurul Fajri Dodon Turianto Nugrahadi Dwi Kartini Dwi Kartini, Dwi Dzira Naufia Jawza Erdi, Muhammad Erlianita, Noor Faisal, Mohammad Reza Fatma Indriani Fatma Indriani Favorisen R. Lumbanraja Febrian, Muhamad Michael Friska Abadi Haekal, Muhammad Haekal, Muhammad Hafizah, Rini Hermiati, Arya Syifa Herteno, Rudy Huynh, Phuoc-Hai Ichwan Dwi Nugraha Indriani, Fatma Irwan Budiman Irwan Budiman Itqan Mazdadi, Muhammad Ivan Sitohang Jumadi Mabe Parenreng Keswani, Ryan Rhiveldi Lilies Handayani M. Khairul Rezki Mafazy, Muhammad Meftah Mariana Dewi Muhamad Fawwaz Akbar Muhammad Al Ichsan Nur Rizqi Said Muhammad Alkaff Muhammad Darmadi Muhammad Fauzan Nafiz Muhammad Haekal Muhammad Haekal Muhammad Ikhwan Rizki Muhammad Itqan Mazdadi Muhammad Mursyidan Amini Muhammad Nadim Mubaarok Muhammad Reza Faisal, Muhammad Reza Muhammad Rofiq Muliadi Muliadi Muliadi Muliadi Muliadi Muliadi Muliadi Muliadi Muliadi Musyaffa, Muhammad Hafizh Nafiz, Muhammad Fauzan Noryasminda Nugraha, Muhammad Amir Nurcahyati, Ica Nurlatifah Amini Okta Muthia Sari Purwoko, Agus Putra, Aditya Maulana Perdana Radityo Adi Nugroho Rahmat Ramadhani Rahmat Ramadhani Rahmatullah, Satrio Wibowo Ramadhani, Rahmat Ratna Septia Devi Regina Reza Faisal, Mohammad Rizki, M. Alfi Rozaq, Hasri Akbar Awal Rudy Herteno Rudy Herteno Safitri, Yasmin Dwi Said, Muhammad Al Ichsan Nur Rizqi SALLY LUTFIANI Salsha Farahdiba Saputro, Setyo Wahyu Siena, Laifansan Siti Aisyah Solechah Siti Napi'ah Suci Permata Sari Sulastri Norindah Sari Tajali, Ahmad Totok Wianto Vivi Nur Wijayaningrum Wahyu Caesarendra Wayan Firdaus Mahmudy Winda Agustina Yanche Kurniawan Mangalik YILDIZ, Oktay Yusuf Priyo Anggodo Zamzam, Yra Fatria