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All Journal Bulletin of Electrical Engineering and Informatics Jurnal Penelitian Pendidikan Kreano, Jurnal Matematika Kreatif-Inovatif International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics Buletin Ilmiah Sarjana Teknik Elektro Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Manajemen Transportasi & Logistik (JMTRANSLOG) Journal of Soft Computing Exploration Devotion: Journal of Research and Community Service Unnes Journal of Mathematics Education Unnes Journal of Mathematics Journal of Advances in Information Systems and Technology Proceeding ISETH (International Summit on Science, Technology, and Humanity) Jurnal Inovasi Pengabdian dan Pemberdayaan Masyarakat Innovative: Journal Of Social Science Research Recursive Journal of Informatics Scientific Journal of Informatics
Endang Sugiharti, Endang
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Public Health Social Sciences Other

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Journal : Journal of Soft Computing Exploration

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Optimization of support vector machine using information gain and adaboost to improve accuracy of chronic kidney disease diagnosis Listiana, Eka; Muzayanah, Rini; Muslim, Much Aziz; Sugiharti, Endang
Journal of Soft Computing Exploration Vol. 4 No. 3 (2023): September 2023
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v4i3.218

Abstract

Today's database is growing very rapidly, especially in the field of health. The data if not processed properly then it will be a pile of data that is not useful, so the need for data mining process to process the data. One method of data mining used to predict a decision in any case is classification, where in the classification method there is a support vector machine algorithm that can be used to diagnose chronic kidney disease. The purpose of this study is to determine the level of accuracy of the application of information gain and AdaBoost on the support vector machine algorithm in diagnosing chronic kidney disease. The use of information gain is to select the attributes that are not relevant while AdaBoost is used as an ensemble method commonly known as the method of classifier combination. In this study the data used are chronic kidney disease (CKD) dataset obtained from UCI repository of machine learning. The result of experiment using MATLAB applying information gain and AdaBoost on vector machine support algorithm with k-fold cross validation default k = 10 shows an accuracy increase of 0.50% with the exposure of the result as follows, the support vector machine algorithm has accuracy of 99.25 %, if by applying AdaBoost on the support vector machine has an accuracy of 99.50%, whereas if applying AdaBoost and information gain on the support vector machine has an accuracy of 99.75%.
Co-Authors Abas Setiawan Adha, Nugraha Saputra Adi, Pungky Tri Kisworo Adi, Pungky Tri Kisworo Afifah, Eka Nur Afifah, Eka Nur Ahmad Solikhin Gayuh Raharjo Al Hakim, M. Faris Alamsyah - Amin Suyitno Anggara, Dian Christopher Anggyi Trisnawan Putra Arief Broto Susilo Astuti, Winda Try Astuti, Winda Try Asyrofiyyah, Nuril Atikah Ari Pramesti, Atikah Ari Auni, Ahmad Ramadhan Budi Prasetiyo, Budi Choirunnisa, Rizkiyanti Clarissa Amanda Josaputri, Clarissa Amanda Devi, Feroza Rosalina Devi, Feroza Rosalina Dian Tri Wiyanti Dwijanto Dwijanto, Dwijanto Dwika Ananda Agustina Pertiwi Fitriana, Erma Nurul Florentina Yuni Arini, Florentina Yuni Hani'ah, Ulfatun Hariyanto, Abdul Heryadi, Muhammad Heri Isa Akhlis Juliater Simamarta Jumanto Unjung Korzhakin, Dian Alya Krida Singgih Kuncoro Kurniawati, Putri Aida Nur Lestari, Dewi Indah Listiana, Eka Malisan, Johny Maulidia Rahmah Hidayah, Maulidia Rahmah Much Aziz Muslim Much Aziz Muslim Muhammad Kharis Mulyono Mulyono Mutiara Hernowo Muzayanah, Rini Nofrisel, Nofrisel Oktaria Gina Khoirunnisa Perbawawati, Anna Adi Perbawawati, Anna Adi Pipit Riski Setyorini Pradana, Dany Pradhana, Fajar Eska Purnamasari, Ratnaningtyas Widyani Ratri Rahayu Riza Arifudin Rizki Danang Kartiko Kuncoro Rofik Rofik, Rofik Rupiah, Siti S.Pd. M Kes I Ketut Sudiana . Sampurno, Global Ilham Sampurno, Global Ilham Sari, Firar Anitya Sekarwati Ariadi, Tiara Subarkah, Agus Sukestiyarno Sukestiyarno Sukmadewanti, Irahayu Sukmadewanti, Irahayu Sulis Eli Triliani, Sulis Eli Supriyono Supriyono Susanti, Eka Lia Sutarti, Sri Sutarti, Sri Umi Latifah Vedayoko, Lucky Gagah Vedayoko, Lucky Gagah Whisnu Ulinnuha Setiabudi, Whisnu Ulinnuha Wijaya, Henry Putra Imam Zaaidatunni'mah, Untsa Zaenal Abidin