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All Journal Semantik Techno.Com: Jurnal Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) JAIS (Journal of Applied Intelligent System) Journal of Development Research Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Penelitian Pendidikan IPA (JPPIPA) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Voice Of Informatics MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Ekonomi, Teknologi dan Bisnis Journal of Computing Theories and Applications Scientific Journal of Informatics Journal of Multiscale Materials Informatics
Purwanto Purwanto
Universitas Dian Nuswantoro
Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Physics Social Sciences Other

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Hyperparameter Tuning Decision Tree and Recursive Feature Elimination Technique for Improved Chronic Kidney Disease Classification Aries Gilang Saputra; Purwanto Purwanto; Pujiono Pujiono
Scientific Journal of Informatics Vol. 11 No. 3: Special Issue
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i3.12990

Abstract

Purpose: This study has the purpose of classifying patients with chronic kidney disease based on specific features and improving the classification models by tuning hyperparameters. This study aims to detect chronic kidney disease at an early stage. Methods: In this study, a machine learning classifier in the form of a decision tree is used to classify chronic kidney disease on the Risk Factor Prediction of Chronic Kidney Disease dataset. After that, the performance of the classifier model is improved by using feature selection, namely Recursive Feature Elimination and Hyperparameter tuning with GridSearchCV. Result: After tests were conducted 3 times namely testing with Decision Tree, Recursive Feature Elimination, and Hyperparameter tuning GridSearchCV which is the proposed method, then compared to other tests. The results from this study is using that method can improve the Decision Tree classifier in classifying chronic kidney disease patients. Novelty: Dataset that have been used in this study is from UCI machine learning repository namely Risk Factor Prediction of Chronic Kidney Disease that have 202 instances and 28 feature and after being processess and conducting test, Recursive Feature Elimination and Hyperparameter tuning GridSearchCV can improve the Decision Tree classifier in classifying chronic kidney disease.
Co-Authors Abdul Syukur Adhe Irham Thoriq Ahmad Riyanto Ahmad Riyanto Ajib Susanto Alzami, Farrikh Anas Syaifudin Anas Syaifudin Aries Gilang Saputra Aris Marjuni Ayu Pertiwi Catur Supriyanto Christy Atika Sari Dian Arif Rachman Didik Hermanto Dwi Puji Prabowo, Dwi Puji Edi Noersasongk Edi Noersasongko Eka Prasetyaningrum Eko Hari Rachmawanto Erna Zuni Astuti Esa Wahyu Andriansyah Fahmi Amiq Fandi Yulian Pamuji Farrikh Al Zami Farrikh Al Zami Fikri Budiman Gunawan Heribertus Himawan Heru Agus Santoso Julius Warih Angkasa Khafiizh Hastuti Md Kamruzzaman Sarker Moch Arief Soeleman Moch. Anjas Aprihartha Muhamad Akrom Muhamad Haris Zuhri Muhammad Misdram Mula Agung Barata Muljono, - Mursalim Mursalim Noorayisahbe Mohd. Yaacob Nova Rijati Nur Wahyu Hidayat Nurhindarto, Aris Pramana, Hendri Julian Pujiono Pujiono Pulung Nurtantio Andono Ricardus Anggi Pramunendar Ridodio Andreuw Meda Ridodio Andreuw Meda Sinaga, Daurat Sutini Dharma Oetomo Viry Puspaning Ramadhan Wresti Andriani Zainal Arifin Hasibuan