The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2024.0150845
PDF

Missing Value Imputation in Data MCAR for Classification of Type 2 Diabetes Mellitus and its Complications

Author 1: Anik Andriani
Author 2: Sri Hartati
Author 3: Afiahayati
Author 4: Cornelia Wahyu Danawati

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 15 Issue 8, 2024.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Type 2 diabetes mellitus (T2DM) is a disease that is at risk for many complications. Previous research on the prognosis of T2DM and its complications is limited to the impact of T2DM on one particular disease. Guidebook for T2DM Management in Indonesia has eight categories of T2DM complications. The purpose of this study is to classify T2DM prognosis into eight categories: one controlled class and seven classes of aggravating disorders. The classification was based on medical record data from T2DM patients at Panti Rapih Hospital in Yogyakarta between 2017 and 2022. The problem is that the medical record data has numerous missing values (MV). The dataset had 29% missing values, classified as Missing Completely at Random (MCAR). This study performed imputation on the dataset prior to categorization. For MV imputation, a variety of imputation methods were used, and their accuracy was measured using Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The best imputation results were utilized to update the dataset. Subsequently, the dataset was used for classification employing several classification methods. The classification results were compared to determine the method with the highest accuracy in this scenario. The Decision Tree method with stratified k-fold cross-validation emerged as the optimal method for this classification. The results revealed an average accuracy value of 0.8529.

Keywords: Missing value; prognosis of diabetes mellitus; missing completely at random; decision tree

Anik Andriani, Sri Hartati, Afiahayati and Cornelia Wahyu Danawati, “Missing Value Imputation in Data MCAR for Classification of Type 2 Diabetes Mellitus and its Complications” International Journal of Advanced Computer Science and Applications(IJACSA), 15(8), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0150845

@article{Andriani2024,
title = {Missing Value Imputation in Data MCAR for Classification of Type 2 Diabetes Mellitus and its Complications},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0150845},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0150845},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {8},
author = {Anik Andriani and Sri Hartati and Afiahayati and Cornelia Wahyu Danawati}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org