Sistem Pakar Deteksi Dini Status Stunting Pada Balita Menggunakan Metode Naive Bayes

Authors

  • Marina Indah Prasasti Universitas Ahmad Dahlan, Yogyakarta
  • Dwi Normawati Universitas Ahmad Dahlan, Yogyakarta

DOI:

https://doi.org/10.30865/mib.v7i3.6443

Keywords:

Toddler, Early Detection, Naive Bayes, Expert System, Stunting

Abstract

A child is defined as stunted if their height for their age is less than -2 Standard Deviations (SD) below the WHO growth criteria Median, and Stunting is caused by inadequate nutrition, frequent illness, and other multidimensional factors. Based on this problem, a study was conducted to develop an early detection Expert System for Stunting status in toddlers using Naive Bayes Method. Data collection was done through a literature review and interviews at the Bantul Health Office. The system development stage includes knowledge acquisition, creating a knowledge base, determining rule bases, creating a decision model with Naive Bayes, and designing the implementation of the system into a computer program. The final stage is to test the feasibility of all functional and non-functional systems through black-box testing, expert judgment, and the system usability scale. The research conducted resulted in an expert system that can detect early Stunting in toddlers and provide appropriate handling solutions and provide probability values for the status of Stunting in toddlers. Based on black-box testing, all functional systems run according to requirements and accuracy with expert judgment produces an accuracy rate of 100% and a system usability scale score of 90, it can be concluded that the expert system that has been built is feasible to use.

Author Biographies

Marina Indah Prasasti, Universitas Ahmad Dahlan, Yogyakarta

Informatika

Dwi Normawati, Universitas Ahmad Dahlan, Yogyakarta

Informatika

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Published

2023-07-23

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