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All Journal Journal of Computer Networks, Architecture and High Performance Computing Jurnal Teknik Informatika (JUTIF)
Fitriya Maharani, Lulu Amnah
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Computer Science & IT Education

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Journal : Jurnal Teknik Informatika (JUTIF)

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Clustering And Classification Of Toddler Stunting Risk Using K-Means And Naive Bayes: A Case Study At Kembaran 1 Community Health Center Fitriya Maharani, Lulu Amnah; Purwadi, Purwadi; Ummul Hidayah, Debby
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 2 (2026): JUTIF Volume 7, Number 2, April 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.2.5420

Abstract

Stunting continues to be a significant public health concern in Indonesia, with a frequency of 17.25% at Kembaran 1 Public Health Center, highlighting ongoing difficulties in early childhood nutrition and growth surveillance. This work seeks to assess and forecast stunting risk in toddlers by employing K-Means clustering and Naive Bayes classification to enhance early detection precision. The K-Means method was utilized on 1,168 toddler growth records to categorize stunting features, whereas the Davies–Bouldin Index (DBI) was employed to evaluate cluster quality. The ideal cluster was attained at k = 8, yielding a DBI value of 4.353, indicating compact and distinctly differentiated clusters. The Naive Bayes classifier subsequently predicted stunting potential with an accuracy of 93.56%, accurately categorizing 218 out of 233 test examples, yielding precision, recall, and F1-score values for the “short” class of 97.41%, 94.95%, and 96.18%, respectively. The findings indicate that the hybrid model successfully combines unsupervised and supervised learning, improving stunting prediction accuracy and cluster interpretability. The research provides a data-centric framework for localized stunting surveillance, aiding community health centers in formulating targeted early treatments and mitigating long-term developmental hazards.
Co-Authors Anggraeni, Eling Sekar Desi Riyanti Pungkas Subarkah Purwadi Purwadi Ranggi Praharaningtyas Aji Ummul Hidayah, Debby