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PRE-PROCESSING DATA ON MULTICLASS CLASSIFICATION OF ANEMIA AND IRON DEFICIENCY WITH THE XGBOOST METHOD

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 17 No. 2 (2023) · pp. 0767–0774

DOI
10.30598/barekengvol17iss2pp0767-0774
ISSN
2615-3017, 1978-7227
Published
2023-06-11
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Anemia and iron deficiency are health problems in Indonesia and globally. In Multiclass Classification, data problems often occur, such as missing data, too many variables, and unbalanced data. Then pre-processing data will be carried out using MissForest imputation, Boruta featuring selection, and SMOTE to help improve the performance of the classification model in predicting a particular class. After the data pre-processing process is carried out, classification modeling will be carried out using the XGBoost algorithm. It was found that when pre-processing the data could improve the performance of the model in predicting multiclass classification for cases of anemia and iron deficiency in women in Indonesia by 0.815 for the accuracy value and 0.9693 for the AUC value

Collaboration network of the authors

25 authors · 61 co-authorship links

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  • Universitas Halu Oleo
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Anang KurniaAffiliation unknown2
I Made SumertajayaAffiliation unknown2
Kusman SadikAffiliation unknown2
Muhammad Nur AidiAffiliation unknown2
Zein Rizky SantosoAffiliation unknown1
Faula ArinaAffiliation unknown1
Utami SyafitriAffiliation unknown1
Embay RohaetiAffiliation unknown1
Abdullah PannuAffiliation unknown1
Budi SusetyoAffiliation unknown1
Anik DjuraidahAffiliation unknown1
Nindi PigithaAffiliation unknown1
Zetil HikmahAffiliation unknown1
Indahwati IndahwatiAffiliation unknown1
Titin YuniartyAffiliation unknown1
Anwar FitriantoAffiliation unknown1
Kristuisno Martsuyanto KapilukaAffiliation unknown1
Farit Mochamad AfendiAffiliation unknown1
Oktaviyani DaswatiAffiliation unknown1
Alona DwinataAffiliation unknown1
Nurhidayah NurhidayahUniversitas Halu Oleo1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://ojs3.unpatti.ac.id/index.php/barekeng/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">PRE-PROCESSING DATA ON MULTICLASS CLASSIFICATION OF ANEMIA AND IRON DEFICIENCY WITH THE XGBOOST METHOD</dc:title>
	<dc:creator>Nurrahman, Fathu</dc:creator>
	<dc:creator>Wijayanto, Hari</dc:creator>
	<dc:creator>Wigena, Aji Hamim</dc:creator>
	<dc:creator>Nurjanah, Nunung</dc:creator>
	<dc:description xml:lang="en-US">Anemia and iron deficiency are health problems in Indonesia and globally. In Multiclass Classification, data problems often occur, such as missing data, too many variables, and unbalanced data. Then pre-processing data will be carried out using MissForest imputation, Boruta featuring selection, and SMOTE to help improve the performance of the classification model in predicting a particular class. After the data pre-processing process is carried out, classification modeling will be carried out using the XGBoost algorithm. It was found that when pre-processing the data could improve the performance of the model in predicting multiclass classification for cases of anemia and iron deficiency in women in Indonesia by 0.815 for the accuracy value and 0.9693 for the AUC value</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2023-06-11</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7740</dc:identifier>
	<dc:identifier>10.30598/barekengvol17iss2pp0767-0774</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications; 0767-0774</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol17iss2year2023</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7740/5938</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 Fathu Nurrahman, Hari Wijayanto, Aji Hamim Wigena, Nunung Nurjanah</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>