Implementasi Teorema Bayes Pada Sistem Informasi Posyandu Dalam Mendeteksi Stunting Pada Balita
 (*)Dedi Gunawan  (Universitas Muhammadiyah Surakarta, Surakarta, Indonesia)
Verania Nur Andika (Universitas Muhammadiyah Surakarta, Surakarta, Indonesia)
(*) Corresponding Author Submitted: May 11, 2023; Published: June 30, 2023 |
Abstract
Abstract–The management of posyandu data in Majegan Village is still carried out manually. This causes health monitoring to be not optimal, especially in detecting stunting in toddlers. One of the efforts to overcome this problem is to provide a posyandu information system that can make it easier for posyandu officers to record and analyze fetal growth until toddlerhood and can detect symptoms of stunting. Through the implementation of Bayes' theorem in a web-based application, stunting symptoms can be observed earlier. Bayes' theorem calculates the values of the symptoms experienced by toddlers so as to obtain the results of probability numbers that can be used to predict stunting in toddlers. System design uses the waterfall method which goes through the stages of SDLC (System Development Life Cycle). After the system was developed, to test the quality of the application and the accuracy of naïve bayes in predicting stunting, two types of testing were carried out, namely black box testing and system usability testing (SUS). The black box test results show that the application functionality runs well with an error percentage of 0%, while the SUS test results show that the application has a usability level at Level B which means the application can be used and help users. Meanwhile, the results of the prediction of naïve bayes produced the model with the highest prediction of 60%.
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