Implementasi Data Mining Untuk Memprediksi Status Gizi Anak Balita Pada Puskesmas Gedung Sari Menggunakan Polynomial Regression

Evi Marlena; Sidik Rahmatullah; Sigit Mintoro; Ngajiyanto Ngajiyanto

doi:10.56327/jtksi.v6i2.1490

Implementasi Data Mining Untuk Memprediksi Status Gizi Anak Balita Pada Puskesmas Gedung Sari Menggunakan Polynomial Regression

Evi Marlena⁽¹⁾, Sidik Rahmatullah⁽²⁾, Sigit Mintoro⁽³⁾, Ngajiyanto Ngajiyanto⁽⁴⁾,

(1) Institut Teknologi Bisnis dan Bahasa Dian Cipta Cendikia
(2) Institut Teknologi Bisnis dan Bahasa Dian Cipta Cendikia
(3) Institut Teknologi Bisnis dan Bahasa Dian Cipta Cendikia
(4) Institut Teknologi Bisnis dan Bahasa Dian Cipta Cendikia

Corresponding Author

Abstract

Predictions of children's nutritional Status can provide important input to. efforts to monitor and intervene in child nutrition, as well as support better decision-making in the field of child health. This study took data from Puskesmas data. Gedung Sari Health Center is a community health center located in Anak Ratu Aji District, Central Lampung Regency. Based on the results and discussion of the data analysis on the data above, related to the prediction of the nutritional status of toddlers at the Gedung Sari Health Center using polynomial regression, a conclusion is obtained. The conclusion of predicting nutritional status using polynomials depends on specific data analysis and modeling and the methods used. However, in general, polynomials can be used to model the relationship between input and output variables in the case of predicting nutritional status. predicted nutritional status of children and total predicted nutritional status obtained Predictions based on age in 2019 = 290,806; Predictions based on nutritional status in 2020 = 68,176; Predictions based on nutritional status in 2021 = 122,239. More research needs to be done to validate and increase the reliability of a prediction and integrate the results into health practice to improve child nutrition monitoring and interventions in the community health center.

Keywords

Nutritional Status of Children Under Five, Data mining, Pyton

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