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September 27, 2025Indonesian Journal of Artificial Intelligence and Data MiningOpen Access

Classification of Big Data Stunting in North Sumatra Using Support Vector Regression Method

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Authors

MSMaradona Jonas SimanullangRRRika RosnellyBRBob Subhan Riza

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Overview

Research classifies big data on stunting using support vector regression, highlighting critical intervention strategies.

Key Points

  • The study achieved an accuracy rate of 91.78% in predicting stunting risk using machine learning methods.
  • Support Vector Regression was utilized to categorize big data, addressing significant factors like malnutrition.
  • Research includes data collection and pre-processing steps essential for accurate predictions and analyses.
  • Findings support the development of targeted intervention strategies to combat stunting among children.

Cite This Study

Simanullang et al. (2024) studied this question.

synapsesocial.com/papers/68d7cc6eeebfec0fc5238f3dhttps://doi.org/10.24014/ijaidm.v8i1.32177
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Classification of Big Data Stunting Using Support Vector Regression Method at Stella Maris Medan Maternity Hospital2024
  2. 2Implementation Of Naïve Bayes Classifier And Support Vector Machine For Stunting Classification2024
  3. 3Performance Optimization of Support Vector Machine with SMOTE for Multiclass Stunting Prediction in Sumedang District, Indonesia2025
  4. 4Comparison of Machine Learning Algorithms for Stunting Classification2025 · 1 citations
  5. 5Stunting Classification Analysis for Toddlers in Bojongsoang: A Data-Driven Approach2024 · 9 citations